Aggregated electronic health record based, massively scalable and dynamically adjustable clinical trial design and enrollment procedure

ABSTRACT

Adequate patient enrollment and participation in different design stages of a clinical trial is facilitated and scaled by dynamically adjusting clinical trial criteria relative to characteristics and conditions of massive numbers of patients whose medical records have been aggregated in databases in compliance with patient privacy and confidentiality laws and regulations. Patient participation results without intervention by multiple providers of healthcare services, and by directly identifying and communicating with qualified patients while maintaining patient privacy and compliance requirements as required by law.

CROSS REFERENCE TO RELATED APPLICATION

This invention is a continuation-in-part of the invention described inU.S. application Ser. No. 13/839,539, filed Mar. 15, 2013, entitledPayment Request-Triggered, Pull-Based Collection of Electronic HealthRecords, invented by the inventor hereof. The subject matter describedin this prior US patent application is fully incorporated herein by thisreference.

FIELD OF THE INVENTION

This invention relates principally to designing clinical trials. Moreparticularly, the present invention relates to a new and improvedprocedure which obtains the medical records of a massive number ofpatients in compliance with patient privacy and confidentiality laws andregulations and which effectively adjusts or reformulates clinical trialcriteria to identify suitable participants when designing a clinicaltrial.

Beneficial effects of the invention include, among other things, anincreased efficiency in designing clinical trials, an enhancedprobability of successfully completing clinical trials, a reduction inthe amount of time and cost required to design and conduct clinicaltrials, and an increased capability of conducting significantly largernumbers of clinical trials for increasingly customized medicaltherapies.

BACKGROUND OF THE INVENTION

Clinical trials are research studies involving humans which evaluate thesafety and efficacy of medical devices and drugs that have been newlydeveloped to treat diseases, ailments and health conditions. Clinicaltrials are typically conducted after the medical device or drug has beentested on animals. Clinical trials typically develop the evidence uponwhich governmental regulatory agencies rely when approving a medicaldevice or drug for human use.

Clinical trials should follow strict scientific standards in order toproduce reliable results. The accuracy of the clinical trial resultsdepends on selecting a representative cohort group of individuals whoare susceptible or responsive to the disease, ailment and healthcondition which the new medical device or drug has been developed totreat. In cases where the medical devices and drugs are intended to beeffective across a broad portion of the human population, for example ameasles vaccine, the cohort group selected for the clinical trial shouldrepresent a broad portion of the human population. On the other hand, adisease, ailment or health condition may afflict only a limited group ofthe general population, due to the specific etiological and healthconditions of that limited group.

It is important to select clinical trial participants which arerepresentative of the afflicted group. For example, the participants maybe required to have specific characteristics of age, gender, ethnicity,allergies, pre-existing and other related medical conditions, and thelike. In this manner, the newly developed drug or medical device istested by a cohort group which is comparable to the same generalpopulation group to which drug or medical device is intended to beapplied. Without performing the clinical trial on the relevant cohortgroup, the results of the clinical trial will not be reliable on thesegment of the human population on which the drug or medical device isintended to be used.

Identifying suitable participants in a reliable clinical trial, andobtaining their participation in a clinical trial, are significantproblems in designing a clinical trial. Information describing themedical condition of patients is protected from disclosure by patientprivacy and confidentiality laws and regulations, and these laws andregulations prohibit the disclosure of most of the important andrelevant information without the consent of the patient, but withoutaccess to the protected patient medical information it is difficult tolocate and identify suitable participants. When the number of suitableparticipants is not readily determinable, it is particularly difficultto design a clinical trial that can be successfully concluded, withoutincurring considerable effort, expense and delay. In the past, there hasbeen no comprehensive database of individuals and their medicalconditions which can be efficiently and lawfully accessed to identifythe most relevant clinical trial participants, and/or to design theclinical trial.

One previous approach to identifying participants for a clinical trialis to use a non-targeted, broadcast or public appeal approach. Aparticular clinical trial is promoted publicly, with the hope that asufficient number of individuals with the desired disease, ailment orhealth conditions will recognize his or her applicability to theclinical trial and respond to the public solicitation. Generallyspeaking, such a non-targeted public appeal obtains the best responsefrom those individuals who are already afflicted with a specificdisease, ailment or health condition. The incentive for response is apotential cure or amelioration of the responder's condition. In general,the responders to such public appeals are only a very small portion ofthe relevant population of the relevant cohort group.

A variant of the public appeal approach involves the use of the worldwide web. The US National Institute of Health (NIH) has a website,clinicaltrial.gov, that presently lists almost 140,000 clinical trialsand studies. Entities which conduct clinical trials are required toregister their clinical trials on this website. The clinical trials arecategorized by various criteria. Interested individuals may investigatethese trials on their own initiative and acquire information to enroll.Currently, the NIH website receives about 60,000 visits each day. Otherwebsites, e.g. TrialX.com and one maintained by the University ofSouthern Florida, are examples of commercially available services thatmatch potential participants with clinical trials.

In these clinical trial situations, which depend upon the responder totake the initiative to enroll, the clinical trial criteria is designatedaccording to disease condition. Interested individuals enter theirmedical history, such as by downloading their medical records, and thenapply them to match the published trial criteria. U.S. Pat. Nos.7,711,580 and 7,251,609, and US patent applications 2001/0051882 and2002/000247, are examples of procedures where interested individualsenter their demographic characteristics and medical profiles and thencompare their information with clinical trial information to determinewhether or not a match exists.

The success of these public appeal approaches depends on the initiativeand knowledge of the prospective clinical trial participants. The valueand success of the public appeal approach is limited by a prospectiveparticipant's limited understanding of the specifics of his or hermedical condition, and an inability to describe those specifics as foundin his or her medical record. Since the potential participants in theclinical trial voluntarily submit their medical and health information,and thereby consent to the disclosure of this otherwise private andprotected information, there is no issue of compliance with patientprivacy and confidentiality laws and regulations.

Another previous approach to identifying relevant participants for aclinical trial involves the organization which designs and possiblyconducts the clinical trial, i.e., a “Clinical Trial Entity,” requestingphysicians, hospitals and other healthcare providers to assist inidentifying potential participants. The Clinical Trial Entity requests aphysician or other healthcare provider to search the health records ofhis or her patients, looking for those patients whose medical conditionsmatch the clinical trial criteria. On arriving at a match, the physicianor healthcare provider is expected to solicit the patient to participatein the clinical trial. US patent applications 2008/0010254 and2010/0088245 are examples of this procedure.

Using the physician or healthcare provider as an intermediary betweenthe clinical trial entity and the potential clinical trial participant,resolves the problem of patient privacy and of accessing full medicalrecords. However, the practical reality is that most physicians andhealthcare providers are unwilling to commit the time and effortrequired to search individual healthcare records and actively solicitsuitable patients to participate in clinical trials. The intermediatedcommunication between suitable patients and their physicians orhealthcare providers must continue until the patient agrees to thedisclosure of his or her identity and medical record to the ClinicalTrial Entity, which requires even further time and effort on the part ofthe intermediating physician or healthcare provider. The requirement forintermediation is a significant impediment in designing efficientclinical trials.

A further difficulty in intermediation between the patient and theClinical Trial Entity is that one physician usually does not possess theentire medical health record of a particular patient. Patientsfrequently see different healthcare providers for different conditionsand at different times of their life, so it is an unusual circumstancefor one healthcare provider to possess a complete medical record of anyparticular individual. The lack of a complete medical record diminishesthe probability of any one physician identifying suitable clinical trialparticipants, and thereby discourages physicians from conducting thesearch in the first place.

A third previous approach to the problem of identifying suitableclinical trial participants involves mining relatively largerepositories of individual healthcare data, such as the records ofhealth insurance companies, pharmacies and medical laboratories. Thistype of data mining attempts to match clinical trial criteria againstpatient medical records. In such circumstances, the patient healthcaredata is annonymized to prevent disclosure of the identity of thepatient. If a match is found, the physician or healthcare providerassociated with that anonymized patient is requested to intermediate bysoliciting his or her patient to participate in the clinical trial.

Mining insurance healthcare claims data for general healthcare trends isa well-established practice. However, the generality of this approach isnot specific enough to identify relevant clinical trial participants.Insurance claims payment data typically lack the specificity and detailrequired to effectively evaluate whether the clinical trial criteria ismatched. Data such as medical laboratory results, drug-to-drug anddrug-to-food contraindications, allergies, medication lists,immunization history, family histories, physician examination notes,discharge summaries, hospitals summaries, long and short term plans ofcare, radiology scans, congenital conditions and genomic markers, arenot typically part of insurance claims payment data, even though thisinformation may be highly relevant or even critical to the clinicaltrial. The success of the healthcare claims data mining approach is alsolimited by the requirement for healthcare providers to intermediatecommunications with their patients. US patent applications 2011/0231422and 2012/0316898 describe this mining procedure in soliciting clinicaltrial participants.

A fourth previous approach to identifying suitable clinical trialparticipants fails to address the practical and legal requirements ofpatient privacy. US patent applications 2012/0035954 and 2004/0034550A1,are examples of this approach. This approach uses computer-basedelectronic queries to directly access the medical records of thehealthcare providers, attempts to match clinical trial criteria with themedical records of the patients, and thereafter directly solicits thesuitable patients. The practical reality is that this process is simplynot compliant with patient privacy and confidentiality laws andregulations. The medical records of patients cannot be accessed exceptwith the consent of the patient. Direct communication with the patientother than through the patient's physician or healthcare provider isalso prohibited. It is improbable that large numbers of patients wouldconsent to having their medical records used in this manner. If apatient did consent, it is unlikely that healthcare providers woulddistinguish the consenting patients from the non-consenting patients inthat provider's own healthcare records.

A further significant practical impediment to this fourth approach isattempting to communicate across a barrier created by the differencesand complexities of the many different electronic systems which containand manage healthcare records. A common electronic format is not used inthe many different electronic medical record-keeping systems ofhealthcare providers, making it very difficult or impossible to extractthe relevant data from the individual records and organize the extracteddata in a common way for efficient usage. Even as electronic medicalrecord keeping systems become more standardized, differences in hardwareand software architectures, version levels, and network and securityprotocols make it inordinately complex to identify these medical recordsand repositories, to gain access to them and to successfully interfacewith them.

The above-described and other constraints have resulted in the clinicaltrial industry performing at a substantially sub-optimal level.According to studies of the Center for the Study of Drug Development(CSDD) at Tuft's University, 90% of all clinical trials are delayedowing to recruitment and retention issues. 15-20% of clinical trialscannot recruit a single patient, and 66% of all clinical trials do notmeet enrollment (recruiting and retaining) requirements. 30% of the timespent in a trial is in recruitment, contributing to 32-40% of the costsat an average of $15,000 per enrollee. Meanwhile, a 2012 CSDD studyestablished that from 2002 to 2012, trial criteria have increased from31 to 50 parameters. Another 2012 study by Scannell and Warringtonestablished that since 1950, for every 1 billion dollars spent, thenumber of drugs approved has halved every 9 years, resulting in acurrent number that is 80 times lower than the number in 1950, due tothe effect of Eroom's law which is analogous to the reverse of Moore'slaw in computing.

The problem of identifying suitable clinical trial participants isfurther exacerbated considerably as drugs and healthcare therapiesbecome more etiologically and genomically customized. In contrast tobaseline therapies which have general effectiveness for broad segmentsof the entire population, drugs and other interventions which arecustomized to specific etiologies (total disease and health states),genomes, bio-markers, molecular biologies, enzyme toxicologies, etc.,are focused on much smaller segments of the general population. Thesenewly developed customized therapies must be tested in clinical trials,but the problems of identifying relevant cohort groups for customizedtherapy clinical trials are exacerbated by the limited access toqualified clinical trial participants who possess the specific healthconditions which make them suitable participants in such clinicaltrials.

For example, a new therapy, even when applied to a specific medicalcondition (such as colorectal cancer), is often found to be effectivefor a percentage of the cohorts of the clinical trial group made up ofindividuals characterized by certain biomarkers. With relatively lowerlevels of effort, compared with developing the original therapy,pharmaceutical and biotech companies may adapt the original therapy toapply to individuals with different biomarkers and thereby achievegreater efficacy for portions of the cohort group. This “branching”capability represents a significant evolution in customizing medicine.However, branching is often constrained by limitations of identifying,accessing and enrolling patients with very specific etiologies asparticipants in clinical trials. Efficiencies in the identification,enrollment and management of clinical trials are critical in theetiological and genomic customization of medical therapies.

The problems of designing effective and relevant clinical trials are notjust limited to identifying individuals who are relevant prospectiveparticipants. Contacting and communicating with the prospectiveparticipants in an effort to enroll them in the clinical trial istime-consuming, whether conducted by the healthcare provider in anintermediary capacity or whether conducted by an administrator of theClinical Trial Entity after obtaining patient consent. Of the number ofqualified prospective participants, only a limited number will respondfavorably to a solicitation, and of those favorably respondingindividuals, an even lesser number will agree to enroll. A significantpercentage of those who agree to enroll will not qualify underapplicable government regulations. A percentage of those who qualifywill withdraw before or after the clinical trial commences. Clinicaltrial entities must anticipate such attrition and reductions, in orderto have a sufficient number of residual participants to complete theclinical trial and achieve meaningful results. In the past, clinicaltrial entities had to make guesses of whether the number of enrolledparticipants was sufficient. Since there was no effective method topredict the number of suitable prospective participants who will enroll,qualify and ultimately complete the clinical trial, excessive numbers ofparticipants were enrolled as a cushion to achieve a successfulcompletion of the clinical trial. In cases where the number ofprospective participants proved to be insufficient after the clinicaltrial commenced, the clinical trial must be terminated prematurely,resulting in an inconclusive outcome.

Similar problems exist with respect to the costs of and time delaysassociated with a clinical trial. At the present time, the costs ofrecruiting clinical trial participants exceeds 30% of the overall costof the trial. The difficulties in identifying relevant clinical trialparticipants, enrolling them, qualifying them, and maintaining theirparticipation throughout the duration of the clinical trial, introducesunpredictable time delays and costs in bringing the medical device,drugs or therapies to market. Since clinical trials constitute asignificant portion of the cost of bringing a newly developed medicaltherapy to market, it is very important to design a clinical trial whichcan be completed and which achieves reliable and sufficient results.Even more importantly, as newly developed therapies become more specificin their utilization, it is important to counterbalance decisionsinvolving the cost of developing a new medical therapy against themarket for that new therapy, to determine whether the developmentaleffort is justified by economic feasibility of marketing that therapy.In the past, a reliable and convenient basis to make economicfeasibility evaluations of new medical therapies has been limited ornonexistent.

The ability to make reliable evaluations of the economic feasibility,and the ability to contain costs while achieving higher efficiencies indesigning a clinical trial, are becoming increasingly important in viewof the number of clinical trials conducted presently and to be conductedin the future. Currently worldwide, there are over fifty thousand activeclinical trials involving about fifteen million participants in anyyear. With the expected expansion of customized therapies, it isanticipated that the number of future clinical trials, and the number ofparticipants involved in such customized therapy clinical trials, couldincrease by two or more orders of magnitude. Efficiencies in the design,enrollment and management of clinical trials are increasingly becomingmore critical to etiological and genomic customization of medicaltherapies.

SUMMARY OF THE INVENTION

This invention involves a process for rapidly and accurately identifyingsuitable clinical trial participants, and thereafter providing areliable basis for predicting the number of suitable participants whowill respond to a solicitation, enroll in the clinical trial, qualify asparticipants and complete the clinical trial. In addition, thecommercial market feasibility of a new medical therapy is determined byestimating the number of patients who would consume the new therapy.After a determination of feasibility, a fast, efficient, reliable andscalable process is established to access, solicit and enroll qualifiedpatients in the clinical trial.

The information upon which to identify prospective participants is basedon the evaluation of a full medical record of each prospectiveparticipant. The full medical records of massive numbers of prospectiveparticipants are aggregated in compliance with patient privacy andconfidentiality laws and regulations, without the intermediation ofhealthcare providers. The access to the full medical records of massivenumbers of prospective participants allows participants to be selectedwho have etiologies and conditions which match more specific clinicaltrial criteria, thereby facilitating economy and reducing cost whendesigning the clinical trial. Once identified, the prospectiveparticipants are efficiently solicited and enrolled.

Interacting with the full medical records of massive numbers of patientsallows the clinical trial criteria to be adjusted or reformulated on adynamic basis while designing the clinical trial. An adequate number ofprospective participants is straightforwardly estimated at each stage ofdesigning the clinical trial. Excessive or insufficient numbers ofprospective participants are avoided without compromising the clinicaltrial, by dynamically adjusting the clinical trial criteria. Dynamicallyadjusting the clinical trial criteria relative to the specificetiological conditions of the prospective participants assures anadequate number of suitable participants from a massive pool ofprospective participants. The identified participants constitute astatistically relevant sample size necessary to achieve a meaningfuloutcome from the clinical trial. Dynamically adjusting the clinicaltrial criteria also contains the cost and minimizes the delay ofdesigning and conducting the clinical trial. The level of specificitywhich is available from dynamically adjusting the clinical trialcriteria is essential when testing customized therapies that have beenaltered from baseline therapies, in order to evaluate efficacy forspecific genomic and etiological characteristics of a limited segment ofthe general population.

An opportunity to wait at each stage of designing the clinical trial isalso available from the present invention. The opportunity to waitincreases the possibility that an adequate number of suitable patientswill become available as potential participants. The pool of potentialparticipants is constantly changing, due to new patients entering themassive pool of potential participants, due to the changing medical andhealth conditions of existing patients in the pool of potentialparticipants, and due to the variable numbers of patients responding torenewed solicitations. The variations in the number and healthconditions of the patients are recognized automatically and continuouslyover time, giving rise to the possibility that waiting will result inidentifying an optimal number of suitable participants.

The costs of researching and developing new medical therapies can alsobe evaluated against the economic feasibility of market consumption ofthese new medical therapies. The costs are evaluated relative toeconomic feasibility thresholds determined from the medical records ofthe massive number of patients. Such evaluations are determined bydynamically adjusting the clinical trial criteria and thereby developinginformation describing the number of patients who will become probableconsumers of the proposed new medical therapy.

In accordance with the invention, a method of designing a clinical trialinvolves aggregating patient medical records of multiple patients toestablish a comprehensive database of the patient medical records of themultiple patients. The medical record of each patient in the databaseincludes information describing the characteristics and conditions ofeach patient. The characteristics and conditions of a first group ofpatients in the database are established by collecting a basicelectronic healthcare record (EHR) of a patient from a healthcareinsurer or an entity responsible for payment of healthcare expenses(Payer). The Payer compensates an individual or healthcare-providingentity (Provider) which delivers healthcare products and services(Healthcare) to each patient in the first group. Patient consent is notrequired to collect payment data from the Payers for the first group ofpatients. The patient payment data is collected under business associateagreements that ensure privacy and confidentiality standards regardingthe use and dissemination of the data. The collected payment data isthen converted to a Basic EHR describing the Healthcare delivered by aProvider to the specific patient.

The characteristics and conditions of a second group of patients in thedatabase are established by collecting more comprehensive EHR datadirectly from a Provider for each instance of the Provider deliveringHealthcare to the patient, in response to the Provider submitting apayment request to the Payer, and aggregating the collected EHR datawith any basic EHR data to create augmented EHR data for each patient inthe second group. The patients in the second group have a relativelyhigher degree of specificity of characteristics and health conditionsthan the patients in the first group. With the database established, theclinical trial criteria is set and compared to the characteristics andhealth conditions of each patient in the first and second groups.Suitable patients are identified from the database who havecharacteristics and health conditions which match the selected clinicaltrial criteria, and the clinical trial is designed and conducted byreference to the identified patients.

Designing the clinical trial is facilitated by aggregating thecomprehensive medical information of massive numbers of patients incompliance with existing patient privacy and confidentiality laws andregulations. The medical information is collected automatically inresponse to payment requests and without intermediation from Providers.Compliance with patient privacy and confidentiality laws and regulationsresults from designating the entity (Aggregator) which aggregates theaugmented EHR data of the second group of patients as a Provider. Withsuch a designation, the augmented EHR data of the patients in the secondgroup is directly collected in an automated manner directly from theother Providers who render Healthcare to the patient. The patientmedical record data is collected under Federal and State statutes, usingFederal standards such as Meaningful Use or other interoperabilityprotocols that allow Providers to collect medical data from otherProviders as part of delivering

Healthcare to a patient.

A central entity in this invention, which functions both as anAggregator and as a Provider, offers the advantage of dis-intermediatingand scaling clinical trials. Aggregation allows a full data set (fullEHRs for a very large set of patients) to be matched against clinicaltrial criteria, and the Provider status of the Aggregator also allowsthe Aggregator to have access to the medical records of patients and tosolicit the patients in the event of a match.

The method of the invention involves identifying a first group ofsuitable patients in the database who have characteristics andconditions which match the selected clinical trial criteria, determiningthat the number of first identified patients is inadequate to continuedesigning the clinical trial, changing at least one of thecharacteristics or conditions of the clinical trial criteria to createadjusted or reformulated clinical trial criteria, and identifying asecond group of suitable patients from the database who havecharacteristics and conditions which match the reformed clinical trialcriteria. In such circumstances, the second identified patients differin number from the first identified patients. The clinical trial is thendesigned and conducted by reference to the second group of suitablepatients.

In addition, the number of patients and their medical records in thedatabase are continuously changed or updated as the characteristics andconditions of the patients continuously change and patients continuouslyreceive Healthcare. When the number of identified second patients isinadequate to continue designing the clinical trial, the procedureoffers the opportunity to wait for the patient medical records toupdate. Thereafter, matching the trial criteria with the updateddatabase permits the identification of a different member of suitablepatients who have characteristics and health conditions which match theclinical trial criteria. The possibility of changing the number ofsuitable patients identified after the patient records have updated, mayfacilitate designing the clinical trial.

These features of the invention permit determinations of whether anadequate number of suitable patients are identified at the solicitation,participation, enrollment and initiation stages of the clinical trialdesign procedure. The economic or market feasibility of developing a newmedical therapy is also determined by use of the clinical trial criteriaand the relative proportions of patients in the different groups ofpatients in the database.

The health condition or etiology of the patient can be further augmentedbeyond the Basic and Augmented EHR databases by including genomic andpost-genomic characteristics to the database. These additionalcharacteristics are utilized similarly to match clinical trial criteriaand determine the feasibility for a clinical trial.

Other aspects and features of the invention, as well as a more completeunderstanding of the present invention and its scope may be obtainedfrom the accompanying drawings, which are briefly summarized below, fromthe following description of presently a preferred embodiments of theinvention, and from the appended claims.

BRIEF DESCRIPTION OF THE DRAWINGS

FIGS. 1A, 1B, 1C and 1D collectively constitute a flow chart of actionsinvolved in a method or procedure of designing a clinical trial, inwhich the present invention is embodied.

FIG. 2 is a block diagram of exemplary data processing and communicationcomputer systems maintained by a Clinical Trial Entity and anAggregator, and a public communication network, all of which are used infacilitating execution of certain aspects of the procedure shown inFIGS. 1A-1D.

FIG. 3 is a block diagram showing entities, actions and communicationsinvolved by an Aggregator in aggregating and establishing acomprehensive database of patient medical records for a massive numberof patients, in accordance with a part of the procedure shown in FIGS.1A-1D.

DETAILED DESCRIPTION

The present invention is embodied in a method or procedure 20 ofdesigning clinical trials, shown in FIGS. 1A-1D. In general, theprocedure 20 involves establishing a comprehensive database of patientmedical records at 22 for a massive number of patients, for examplemillions of patients, by aggregating the medical records in a database.The degree of detail or specificity of the medical record of eachpatient varies, so the database established at 22 for some patientsextends only to a basic health record, while other patients have a moreextensive medical record that also includes details derived from therecords of the Healthcare (medical products and services) delivered byProviders (individuals and entities that supply Healthcare), while stillother patients have an even more comprehensive medical record that alsoincludes such additional information as genomic sequences and markersand other more detailed descriptions of specific health and medicalcharacteristics. Establishing the comprehensive database of patientmedical records at 22 involves aggregating and using the patient medicalrecords in compliance with patient privacy and confidentiality laws andregulations. One technique of aggregating the medical records of massivenumbers of patients is described generally below in connection with FIG.3, and more specifically in the above referenced prior U.S. patentapplication Ser. No. 13/839,539.

The specific health and medical conditions desired in the participantsin the clinical trial are selected as clinical trial criteria at 24.Trial criteria are selected from a predefined table of criteria. Thecriteria correspond to specific patient characteristics, patientconditions and health and medical information which will typically becontained in the medical records of patients. The trial criteria includedata such as age, gender, address, race, previous diseases, previousmedical procedures, drug histories, allergies, congenital conditions,epidemiologies, and genome characteristics, and the like, among otherthings. These criteria are referred to herein as etiologies. The trialcriteria/etiologies are reflected in the database established at 22.

A committee of medical and regulatory experts establishes thecharacteristics which define the entries in the predefined trialcriteria table. The committee of experts also approves any changes tothe criteria table. In this manner, the committee of experts assuresthat there is a singular medically-specific definition and designationfor each particular criteria/etiologies. The use of specificnomenclature assures that each clinical trial criteria may be designatedand identified only in a singular manner, thereby avoiding confusionamong the various criteria/etiologies. The committee of medical andregulatory experts which define the entries in the trial criteria tableare employed by or associated with the entity which aggregates thepatient medical records of multiple patients in the database, referredto herein as an “Aggregator.” The function of the committee of medicaland regulatory experts employed by the Aggregator is to assure that thecriteria/etiologies of the patients in the database are specificallydesignated and free of substantial confusion with and distinguishablefrom other criteria/etiologies.

An Administrator of the entity which designs and possibly conducts theclinical trial, herein referred to as a “Clinical Trial Entity,” selectsa combination of multiple entries from the pre-defined criteria table toestablish the initial trial criteria at 24 which is used in designingthe clinical trial. The Administrator of the Clinical Trial Entity maybe aided in the selection at 24 by other medical experts employed by theClinical Trial Entity. The initial trial criteria is selected by theAdministrator at 24 with the view toward identifying those potentialparticipants in the clinical trial which will provide the most reliableinformation for evaluating the efficacy of the newly developed drug ortherapy which is the subject of the clinical trial. Changes to theselected clinical trial criteria may occur as a result of the dynamicadjustment features of the procedure 20, which are described below, asoverseen by the Administrator and possibly by medical experts employedby the Clinical Trial Entity.

The clinical trial criteria selected at 24 are thereafter compared bythe Aggregator at 26 with the medical records of the patients in thedatabase established at 22. The comparison is facilitated as a result ofthe Aggregator organizing the specific criteria/patient etiologies inthe database established at 22 so that the etiologies may be searchedand matched efficiently. At 28, a number of suitable patients withcharacteristics and health conditions matching the clinical trialcriteria selected at 24 is determined. The number of suitable patientswith matching criteria determined at 28 is thereafter used in theprocedure 20 as the basis to design and organize the clinical trial.

In order to maintain patient privacy, the Administrator of the ClinicalTrial Entity interacts with a Liaison from the Aggregator in order toaccomplish the comparison at 26, thereby preventing access by theClinical Trial Entity to the database of information created by theAggregator. In general, the Administrator of the Clinical Trial Entitysupplies the list of clinical trial criteria to the Liaison of theAggregator. The Liaison oversees the comparison executed by theAggregator and supplies the number of suitable patients with matchingetiologies to the Administrator. The names of the patients in thedetails of their medical records are not disclosed at this stage of theprocedure 20. Consequently, the private medical information of thepatients is maintained confidential by the Aggregator, and is notdisclosed at this stage of the procedure 20. At this stage of theprocedure, the Administrator and the Clinical Trial Entity areprincipally interested in the numbers of patients having health andmedical conditions which match the clinical trial criteria.

The function of the Liaison is predominantly automated to serve as aninterface between the Clinical Trial Entity and the Aggregator. TheAdministrator's functions are facilitated by computer systems and userinterfaces, provided either by the Clinical Trial Entity or theAggregator, to automate as many of the tasks performed by theAdministrator as are feasible. Manual or human tasks that need to beperformed, particularly those requiring interfacing between the ClinicalTrial Entity and the Aggregator, are generally handled by either theAdministrator or the Liaison. Given the number of trials managedconcurrently by the Aggregator, most of the activities of the Liaisonand the Administrator will be automated.

As is discussed in more detail below, certain stages of the clinicaltrial design procedure 20 involve dynamically adjusting the clinicaltrial criteria selected at 24. Among other things, dynamic adjustment ofthe clinical trial criteria facilitates a determination of the economicfeasibility of developing the new medical therapy and facilitatesefficiently and effectively designing and completing the clinical trial.In general, the dynamic adjustment aspects of the procedure 20 involveiteratively changing the selected clinical trial criteria at 24 toevaluate and optimize the number of suitable participants determined at28, in a way which ensures an efficient and effective design of theclinical trial.

The dynamic adjustment capability of the procedure 20 also facilitates adetermination of the economic feasibility of researching, developing andmarketing the new medical therapy. In general, economic feasibility isaccomplished by the Clinical Trial Entity at 30, by extrapolating thenumber of suitable patients determined at 28 to obtain a reasonableexpectation of the total number of patients in the entire populationwhich possess the etiological characteristics which will be served bythe newly developed medical therapy. As such, the number of patientsextrapolated at 30 constitute a reasonable approximation of the economicmarket for consuming the newly developed therapy.

The extrapolation performed at 30 is based on the numbers of patientsand their medical records in the database established at 22. After theextrapolation at 30, a determination is made at 32 as to whether asufficient market of consuming patients exists to justify the costs ofresearching and developing the new medical therapy. If there isinsufficient market feasibility, as determined by a no (1) negativedetermination at 32, an affirmative determination at 34 results in theprocess flow moving to 24, where the clinical trial criteria is adjustedby changing the degree of specificity of the clinical trial criteria.Then, using the adjusted clinical trial criteria, the actions identifiedat 26, 28, 30 and 32 are performed again to evaluate market feasibility.

The adjustment which results from the no (1) negative determination at32 will increase the number of qualified patients with matchingcriteria, determined at 28, when the level of specificity of theclinical trial criteria at 24 is decreased by eliminating one or more ofthe patient etiologies previously selected from the clinical trialcriteria. On the other hand, the adjustment can also decrease the numberof patients with matching criteria by increasing the level ofspecificity of the clinical trial criteria. Dynamically adjusting theclinical trial criteria in this manner to increase or decrease the levelof specificity of etiologies permits exploring the limits of theeconomically feasible market for the new medical therapy.

Another important feature of the procedure 20 relates to the type ofaction which may be taken in response to a circumstance where adjustingthe clinical trial criteria does not result in meeting a desiredthreshold. When determining economic feasibility, an inability toachieve sufficient economic feasibility after adjustment of the clinicaltrial criteria is represented by a no (2) negative determination at 32.In that case, the procedure 20 offers an opportunity to wait at 38 untilfor a desired amount of time determined at 40. A decision to wait at 38for a desired amount of time at 40 allows more patient medical recordsto be accumulated in the database established at 22, and allows themedical records of patients previously in the database to change due tochanges in the health and medical conditions of patients occurring overtime. The opportunity to wait at 38 and 40 is a viable option becausethe database established at 22 is updated on a continuous basis by theAggregator with the addition of medical records of new patients andchanges to the health and medical conditions of existing patients.

Waiting the desired amount of time, as determined at 38 and 40, offersthe possibility that the updated information in the database establishedat 22 will contain adequate information to overcome the thresholdcircumstance which the previous dynamic adjustment of the clinical trialcriteria could not overcome. If the decision is to wait at 38, theprocedure 20 is again executed at the expiration of the time establishedat 40. Executing the procedure 20 after the wait time determines whetheran adequate number of new patients and patients with changed medicalrecords are now present in the database established at 22 to evaluateeconomic feasibility, or, as discussed below, to change the number ofparticipants in the clinical trial. Of course, if the decision at 38 isnot to wait, the procedure 20 ends at 42. The Administrator can also, atany point, interrupt the wait time period and thereby cause itsexpiration. The process flows, in this case, would follow the sameroutes as though the wait time had expired without interruption.

The opportunity for the Clinical Trial Entity to dynamically adjust theclinical trial criteria to meet significant thresholds at each step ofdesigning the clinical trial significantly improves the typicalprocedure involved in designing and conducting a successful clinicaltrial. The information available from dynamic adjustment optimizes thedesign of each stage of the clinical trial. In general and in referenceto FIGS. 1B-1D, dynamic adjustment is used to increase or decrease thenumber of suitable identified patients at 44, 46 and 48; to evaluatewhether the number of identified patients constitutes an adequate poolof participants to complete the clinical trial at 50, 52 and 54; toincrease or decrease the number of patients who respond to a directsolicitation for participation in the clinical trial at 56, 58, 60 and62; to evaluate whether the number of favorably responding patientsconstitutes an adequate pool of favorably responding patients to qualifyand complete the clinical trial at 64, 66 and 68; to increase ordecrease the number of favorably responding patients who actually enrollas qualified participants in the clinical trial at 70, 72, 74 and 76;and to evaluate whether the number of enrolled patients constitutes anadequate pool of participants to complete the clinical trial at 78, 80and 82. At each of these procedural stages of designing the clinicaltrial, there is an opportunity to wait at 38 for the expiration of apredetermined time at 40. Waiting might facilitate meeting the desiredthresholds which were otherwise not possible to meet prior to theexpiration of the waiting time, or to end the procedure 20 at 42.Satisfying all of these conditions or thresholds when designing theclinical trial facilitates successfully conducting the clinical trial at84.

The capability to adjust the scope of the clinical trial by adjustingthe trial criteria to achieve an adequate number of participants foreconomic feasibility and to facilitate the successful completion of theclinical trial, at each of the many stages of designing the clinicaltrial, is a significant improvement over prior clinical trial designtechniques. Known prior techniques do not provide a convenientopportunity to adjust, in an informed manner, the scope of the clinicaltrial on a dynamic basis at each of the principal stages of designingthe clinical trial. As a consequence, prior clinical trials are subjectto more uncertainty with respect to cost, efficiency and successfulconclusion.

In contrast, dynamically adjusting the clinical trial criteria andevaluating the results of such adjustments relative to thresholds ateach stage of the clinical trial procedure 20, allows the clinical trialdesign to go forward with optimal efficiency, thereby avoiding excessivecosts and unexpected time delays, while still ensuring that the resultswill provide enough reliable information to determine efficacy of thenewly developed therapy. Reducing the cost of the clinical trial, andincreasing the efficiency with which the clinical trial is conducted,are important factors in developing a new medical therapy, because about30% of the cost of developing a new medical therapy is presentlyconsumed by conducting the necessary clinical trials. Reducing the costsof the clinical trial without compromising the reliability of theresults is a significant improvement over past methods of designingclinical trials.

In the past, clinical trials were not designed through the use of acomprehensive database of patient medical records that was establishedin compliance with patient privacy and confidentiality laws andregulations. Past clinical trials had no known capability to iterativelyadjust the scope of the clinical trial by changing the clinical trialcriteria using a comprehensive database of patient medical records. As aconsequence, prior clinical trials typically enrolled an excessive orinsufficient number of participants. Enrolling an excessive number ofparticipants increased the cost of the clinical trial without achievinga comparable increase in information by which efficacy could bedetermined. Enrolling an insufficient number of participants led to apremature termination of the clinical trial due to the natural tendencyof some participants to drop out before the clinical trial wascompleted, or led to the clinical trial delivering an insufficientamount of information by which to determine efficacy on a reliablebasis.

The comprehensive database of patient medical records established by theAggregator at 22 makes possible the dynamic adjustment of the scope ofthe clinical trial. Without a comprehensive database of medical patientrecords, there is no efficient capability to compare specificallyselected clinical trial criteria with the etiologies of massive numbersof patients. Accordingly, the benefits of the present invention will notbe fully realized without the ability to aggregate and establish acomprehensive database of medical records of many patients.

The aggregation of the patient EHRs also allows the Aggregator and theClinical Trial Entity (once patient consent has been obtained), todirectly push clinical trial information and solicitation to qualifiedpatients in a very specifically targeted manner while maintaining theconfidentiality of the patient. This approach is a significantimprovement over current techniques of pulling in patients based on abroad notice of a clinical trial with the expectation that the patientwill, on his or her own initiative or through an intermediatedsolicitation by a Provider, find his or her way to a clinical trial.

The comprehensive database of patient medical records, and the abilityto dynamically adjust the clinical trial criteria relative to thepatient health and medical conditions recorded in that comprehensivedatabase, coupled with the capability to wait for changes in thepatient's medical records or in the number of patients, and the abilityto directly target and solicit qualified patients, are significantimprovements in designing clinical trials and in overcoming the priordetrimental aspects of designing clinical trials, as described ingreater detail below.

The procedure 20 is preferably executed with the aid of two separatedata processing and communication computer systems 90 and 91, shown inFIG. 2. The computer system 90 is maintained and controlled by theAggregator to establish and update the comprehensive database of patientmedical records 22 (FIG. 1A). The other computer system 91 is controlledby the Clinical Trial Entity to design the clinical trial. The separatecomputer systems 90 and 91 prevent the Clinical Trial Entity fromaccessing the protected medical records of the patients aggregated bythe Aggregator. Similarly, the Aggregator is prevented from accessingthe protected aspects of the clinical trial procedure 20.

The Aggregator computer system 90 has a capability to solicit patients(56, FIG. 1B) to participate in the clinical trial designed by theClinical Trial Entity, until such time as the patient agrees toparticipate in the clinical trial and gives consent to the Aggregator todisclose his or her identity and/or medical records to the ClinicalTrial

Entity. Once the consent is given, the Clinical Trial Entity computersystem 91 has the capability to directly communicate and start theenrollment process (70, FIG. 1C) with those patients who have giventheir consent. Specifically and only for these patients, the ClinicalTrial Entity may, if required, receive copies of the medical recordsfrom the Aggregator computer system 90. The Clinical Trial Entitycomputer system 91 will typically be used to enroll consenting patientsin the clinical trial (70 and 71, FIG. 1C), but the Clinical TrialEntity may also request the Aggregator to assist with patientenrollment, in which case Aggregator computer system 90 may also have acapability for enrollment.

The computer systems 90 and 91 automatically execute those aspects ofthe procedure 20 which do not require human intervention. TheAdministrator 100 interacts with the computer system 91 at humandecision points in the procedure 20 through a communication interface101, while executing the Clinical Trial Entity aspects of the procedure20. The Liaison 102 interacts with the computer system 90 at humandecision points in the procedure 20 through a communication interface103, while executing the Aggregator aspects of the procedure 20. TheAdministrator 100 and the Liaison 102 may establish a directcommunication link 104 with each other, and/or the Administrator 100 andthe Liaison 102 may also communicate over a public communicationnetwork, such as the internet 106, through their respectivecommunication interfaces 101 and 103. As described earlier, tofacilitate the scale of clinical trials conducted, the functions of theAdministrator 100 and the Liaison 102 are preferably automated to themaximum extent possible.

The Administrator 100 communicates with the Liaison 102 to request theAggregator to execute the instructions of the Clinical Trial Entity whendesigning the procedure 20, under circumstances where access to andinteraction with the patient medical records must be kept confidential,such as when suitable identified patients are solicited to participatein the clinical trial. The Liaison 102 electronically communicates withthe patients over the internet 106 when issuing solicitations toparticipate in the clinical trial, when the solicited patient has acommunication capability through the internet 106. In thosecircumstances when the solicited patient does not have an internetcommunication capability, the Liaison 102 issues communications andsolicitations by an alternative communication procedure, such as regularpostal service. The Administrator 100 electronically communicates overthe internet 106 to transmit information and instructions to thosepatients who have consented to allow communication of their identityand/or medical records with the Clinical Trial Entity, and to enrollthose suitable consenting patients as participants in the clinicaltrial.

The Administrator 100 and the Clinical Trial Entity also use theinternet 106 as much as possible when qualifying enrolled patients andin conducting the clinical trial. An effective communication capabilitybetween the Administrator 100 and the Liaison 102 coordinates thefunctionality of the computer systems 90 and 91 when performing theclinical trial procedure 20. It is advantageous from an efficiencystandpoint for as many patients 120 as possible to be connected forcommunication through the internet 106 to facilitate efficiency indesigning the clinical trial. Efficiency is facilitated by directcommunications over the internet 106 to solicit suitable patients toparticipate in and enroll in the clinical trial, to enroll in theclinical trial, to qualify for the clinical trial and in some cases toreport results from participating in the clinical trial.

Patients 120 may also communicate over the internet 106 with either ofthe computer systems 90 and 91, respectively, under appropriatesafeguards where those communications do not violate the privacy ofmedical records or adversely influence the procedure 20 performed by theClinical Trial Entity and the Aggregator. The patients 120 may alsocommunicate with the Administrator 100 and/or the Liaison 102 underappropriate circumstances to prevent the disclosure of confidentialpatient information. Patient communications from the internet 106 aremanaged so as to not interfere with aspects of the functionalitycontrolled by the Aggregator and of the Clinical Trial Entity.

The Aggregator computer system 90 includes one or more data processingunits 92, each of which is connected to banks of separate memories 94,96, 98 and 99 by a system bus 108. Each of the memories 94, 96, 98 and99 is used to store the data describing the medical records of thepatients. The memories 94, 96, 98 and 99 constitute the comprehensivedatabase of patient medical records established at 22 (FIG. 1A). All ofthe patients which make up the comprehensive database (22, FIG. 1A) areidentified in one or more of the memories 94, 96, 98 and 99. A commonunique patient identification identifies the patients in the memories.Although memories 94, 96, 98 and 99 are shown as separate, they may becombined into separately identifiable portions of a single large memory.

The memory 94 constitutes a basic electronic health record (EHR) vault,the memory 96 constitutes an augmented EHR vault, the memory 98constitutes a genomic vault and the memory 99 collectively refers toother patient characteristics that may be collected, such as the epigenome. The data describing the medical record of each patient in eachvault 94, 96, 98 and 99, varies according to the level of specificity ordetail describing the patient's characteristics and health conditions,i.e. the patient's etiology, and according to the level of participationby the patient.

The EHR vault 94 stores the EHR for each patient identified in thatvault 94. The patient and his or her EHR identified in the EHR vault 94represent the lowest level of patient participation in the comprehensivedatabase. The basic EHR includes the patient name, gender, address, dateof birth, the date of a medical procedure, a disease code for thecondition treated and a code for the procedure performed. Pre-existingstandards define the disease and procedure codes. The information forthe EHR vault 94 is derived from healthcare claims sent by a Provider toa Payer to obtain payment for Healthcare rendered to the patient. Thoseindividuals and entities which deliver healthcare products and servicesto a patient are referred to herein as Providers. Providers includedoctors, doctor offices, clinics, surgical centers, laboratories,hospitals, urgent care centers, pharmacies, rehabilitation centers andphysical therapists. Healthcare constitutes both services and productsdelivered to a patient by a Provider. A Payer is a healthcare insurer oran entity responsible for paying the Provider for rendering Healthcareto a patient.

The data in the basic EHR vault 94 is collected from claims repositoriesmaintained by Payers. Since the information in the basic EHR vault is anaggregation of claims records from various Payers, no consent of thepatient is required to collect this claims data; the collection and useof the selected healthcare claims data is part of the businessrelationship between the Aggregator and the Payer. Claims data isregularly used to develop information describing current health trends.Collection and use of this claims data under accepted guidelines andbusiness associate agreements is not a violation of patient privacy andconfidentiality laws and regulations.

The augmented EHR vault 96 stores an augmented EHR for each patientidentified in that vault 96. The information contained in the augmentedEHR vault 96 includes all of the basic EHR information plus theadditional information obtained from the records of a Provider whodelivered Healthcare to a patient. This additional information includesdata such as lab results, drug to drug allergies, food to drugallergies, food to food allergies, general allergies, dischargesummaries, immunizations, untreated disease codes, family histories, andcongenital conditions (e.g., Gilbert's Syndrome). This additionalinformation is derived directly from the records of each Provider whorenders Healthcare services to that patient, as is discussed below indetail in conjunction with FIG. 3. Patient consent is required topopulate the augmented EHR vault 96. In addition, information containedin the augmented EHR vault 96 also includes health monitoring datasupplied by the patient. Health monitoring data is currently availablefrom consumer apps running on smartphones and other home andclose-to-patient based diagnostics programs.

The information contained in the augmented EHR vault 96 is obtained froma local clinical computer system of the Provider which rendersHealthcare to the particular patient, in response to an electronicrequest communicated to that Provider. In response, the clinicalcomputer system (FIG. 3) of the Provider communicates the patient'shealthcare information which is then recorded in the augmented EHR vault96. The communication of the healthcare information in this manner maycomply with the Meaningful Use (MU) standard required by US law or withother interoperability standards or arrangements.

A genomic vault 98 stores even more comprehensive information describingthe characteristics and medical and health conditions of certainpatients. The genomic vault 98 contains some or all of the sequencedgenome for the patient, as well as markers for some specific genomicconditions for which tests are currently available, such as theAlzheimer marker, APOE e2/e4, the breast cancer marker, BRCA 1 & 2, andthe like. Genomic information is typically beyond the healthcare recordinformation contained in the augmented EHR vault 96 for each patient.However, if such genomic information is procured for a patient, it isstored in the genomic vault 98. In most cases, the patient will undergothe necessary tests and evaluations to derive and thereafter supply thegenomic information for inclusion in the genomic vault 98. The consentof the patient is required to populate the genomic vault 98 with thepatient's genomic information, unless that information is available fromthe health care records of the patient's Provider.

Other vaults 99 are intended to anticipate even more specific andindividualized information associated with each patient, such as the epiGenome. A number of vaults 99 are provided, and each of them may belimited to a specific and individualized health or medical condition orcharacteristic of a patient. In general, the consent of the patient isrequired to populate the vaults 99 with that patient's information.

Payers encourage patients to consent to delivering their medical recordsto the augmented EHR vault 96. Patients who give this consent are morelikely to consent to having their genome mapped and included along withtheir augmented EHR in the genomic record. Additionally, these patientsare more likely to actively monitor their health by periodicallycollecting health data and communicating that data to enhance theirmedical records. Due to an elevated interest in health, these patientsare usually receptive to monitoring, receiving, evaluating andresponding to solicitations for enrollment as participants in clinicaltrials. Information which is not collected as described in FIG. 3 butwhich is supplied by patients, is entered in the vaults 94, 96, 98 and99 by the Aggregator through the communication interface 103.

The augmented EHR vault 96 has more specific etiological informationthan the basic EHR vault 94, but fewer numbers of patients areidentified in the augmented EHR vault 96 than the greater number ofpatients identified in the basic EHR vault 94. The genomic vault 98 haseven more specific etiological information for each of the patientsidentified in that vault than the etiological information for each ofthe patients identified in the augmented EHR vault 96, but the number ofpatients identified in the genomic vault 98 is typically lesser than thenumber of patients identified in the augmented EHR vault 96. The vaults99 which store even more specific etiological information of certainpatients, typically identify an even fewer number of patients than thenumber of patients identified in the genomic vault 98.

The differing number of patients in each of the vaults 94, 96, 98 and99, and the differing content of the etiological information describingeach patient, is used in the procedure 20 (FIGS. 1A-1D) to extrapolateand predict certain information which was not previously established orused but which is important to efficiently and effectively design aclinical trial.

The Clinical Trial Entity computer system 91 includes one or more dataprocessing units 110, each of which is connected to a memory 112 whichcontains the code which defines the programming instructions necessaryto perform the aspects of the present invention performed by theClinical Trial Entity, as discussed below. The communication interface101 is connected to control each data processing unit 110.

The details of obtaining the EHR information to populate the augmentedEHR vault 96, as well as establishing the comprehensive database ofmedical records (22, FIG. 1A) in compliance with patient privacy andconfidentiality laws and regulations, are generally described inconjunction with FIG. 3, and are described more specifically in theabove referenced U.S. patent application Ser. No. 13/839,539. Except inthose instances where the actions and communications must be performedby humans, the actions and communications described in FIG. 3 areanticipated to be performed by electronic computer and communicationsdevices which have been programmed to execute the functions described.

The EHRs of the patients 120 are aggregated and augmented automaticallyby the interaction and communication between Providers 122, Payers 124and at least one EHR Aggregator 126. The functionality of the Aggregator126 may be executed by the data processing units 92 of the computersystem 90 (FIG. 2), or may be executed by a separate computer systemwhich delivers the data to the vaults 94 and 96 of the computer system90 (FIG. 2). The Aggregator 126 must attain the status of a Provider, inorder to automatically or otherwise access the health records maintainedby a Provider while complying with patient privacy and confidentialitylaws and regulations. Patients 120 have an incentive to designate theAggregator 126 as a Provider, because the Aggregator 126 will maintain acomplete and accurate medical record of the patient. A complete andaccurate medical record will facilitate the patient receivingappropriate Healthcare. The fact that a new or different Provider mayaccess the augmented EHR vault 96 to provide Healthcare is a furtherincentive to the patient to designate the Aggregator 126 as a Provider.The timely comprehensiveness of the EHR data that is made available fromProviders enhances the quality of Healthcare, and safety of the patient,and serves as an improved basis to manage healthcare costs.

The patients 120, Providers 122, Payers 124 and the Aggregator 126interact with one another by communicating and taking those actionsshown and explained in connection with FIG. 3. For convenience ofillustration and description, FIG. 3 illustrates instances of a singlepatient 120 interacting with a single Provider 122 and that singleProvider 122 interacting with a single Payer 124. In actual practice, asingle patient 120 could interact with multiple Providers 122, and eachProvider 122 could interact with multiple Payers 124.

The patient 120 begins by seeking Healthcare from a Provider 122. Thisrelationship is established in a patient-Provider transaction 128. Thepatient-Provider transaction 128 involves the Provider 122authenticating the identity of the patient seeking the Healthcare, andassures that the EHR will be established for the correctly identifiedpatient.

As part of the patient-Provider transaction 128, the Provider 122delivers Healthcare to the patient 120. In conjunction with deliveringthe Healthcare, the Provider 122 establishes the EHR that describes theHealthcare delivered to the patient. The EHR created by the Provider 122is established in Meaningful Use (MU)-compliant form, and thatMU-compliant EHR is then stored locally in a local memory 134 of theclinical computer system of the Provider 122. Providers are required bylaw to commence using MU digital healthcare standards and specificationswhich establish a format and definition of an EHR. The MU standards alsoestablish a uniform protocol for communication and information exchangeof EHRs between Providers. The principal purpose of the MU standards isto establish a basis for Providers to exchange EHR data about patientsin a timely manner, thereby offering the possibilities of increasedcoordination and quality of Healthcare and safety of the patient, andmanaged healthcare costs. Although in MU is described herein as theprevailing standard for EHR storage and dissemination, other EHR andinteroperability standards and arrangements could be used in accordancewith the invention.

The Provider 122 thereafter seeks payment for the Healthcare deliveredto the patient 120, by submitting a payment request 138 to the Payer 124that is responsible for paying for the Healthcare delivered to thepatient 120. The payment request 138 submitted by the Provider 122 tothe Payer 124 is in a standardized format established by the Payer forpayment requests. The standardized format for payment requests includesinformation which identifies the patient and the Provider, andinformation which contains a basic description of the Healthcaredelivered by the Provider to the patient. This standardized format isrequired by the Payer 124 to evaluate the legitimacy and the extent ofthe payment request. Although not shown, in response to a proper paymentrequest 138, the Payer 124 will send payment to the Provider 122.

The Payer 124 then transmits a payment request trigger 142 to theAggregator 126. The payment request trigger 142 includes theidentifications of the patient and the Provider and a basic descriptionof Healthcare delivered, derived from or based on the informationcontained in the payment request 138. The Aggregator 126 interprets thepayment request trigger as an indication that Healthcare has beendelivered to the identified patient by the identified Provider. Inresponse to the payment request trigger 142, the Aggregator 126commences action to establish, collect and augment an EHR record for theidentified patient, by collecting information from the EHR stored in thelocal memory 134 of the identified Provider 122.

In preparation for establishing, collecting and augmenting the EHRrecord for each identified patient, the Aggregator 126 extracts from thepayment request trigger 142, the identity of the patient, the identityof the Provider, and the basic EHR data contained in the payment requesttrigger 142. The information extracted from the payment request trigger142 is then stored by the Aggregator 126 in the basic EHR memory vault94 (also shown in FIG. 2).

Using the extracted identification of the Provider 122 and the patient120, the Aggregator 126 sends a pull request 152 to the identifiedProvider 122. The pull request 152 includes the identification of thepatient 120, and constitutes a request for the Provider 122 to obtainfrom the local memory 134, the MU-compliant EHR data of the identifiedpatient and to transmit that EHR back to the Aggregator 126. In additionto the identity of the patient, the pull request 152 may also include atleast one aspect of the basic EHR data contained in the payment requesttrigger.

The Provider 122 responds to the pull request 152 in a pull reply 156.The pull reply 156 involves obtaining the MU-compliant EHR data of theidentified patient from the local memory 134 and transmitting that EHRback to the Aggregator 126. The

EHR data transmitted by the Provider constitutes the major part of thepull reply 156 and includes comprehensive information describing theHealthcare delivered to the identified patient. The EHR data returned inthe pull reply is more complete, compared to the basic descriptioncontained in the payment request trigger 142. Accordingly, the EHR dataprovided to the Aggregator 126 in the pull reply 156 is a more completerecord of the Healthcare delivered to the identified patient. A completerecord of the Healthcare delivered to the identified patient by theProvider is permitted under the law because the Aggregator 126 has beendesignated by the patient as a Provider.

With the more complete EHR data in the pull reply 156 from the Provider122, the Aggregator 126 updates the basic EHR data obtained from thepayment request trigger and stored in the basic EHR memory vault 94. Theupdated and more complete EHR data constitutes the augmented EHR recordof the Healthcare delivered to the identified patient by the identifiedProvider. The augmented EHR record for the patient is thereafter storedin the augmented EHR vault 96 (also shown in FIG. 2).

The previously described series of transactions and interactions isrepeated each time a patient obtains Healthcare delivered by a Provider.Each new instance of a Provider delivering Healthcare results inupdating the augmented EHR record of each patient, after the Providersubmits the payment request 138 and the Payer transmits the paymentrequest trigger 142 to the Aggregator 126. In this manner, the EHRrecord of each patient is automatically updated for each instance of anadditional patient-Provider transaction 128. The augmentation of thepatient's EHR record based on the Healthcare previously delivered to thepatient establishes a historically more-complete and contemporaneousaugmented EHR record.

The augmented EHR record of each patient is stored in the augmented EHRvault 96 and is accessible to a Provider 122 for use in conjunction withdelivering future Healthcare. When a new or existing patient 120requests Healthcare from a new or existing Provider 122, apatient-Provider transaction 128 is initiated. The Provider 122authenticates the patient by obtaining the patient's identification.Then, as part of the patient-Provider transaction 128, the Provider 122sends an EHR request 168 to the Aggregator 126. The EHR request 168includes the identification of the patient 120 and the identification ofthe Provider 122. The Aggregator 126 responds to the EHR request 168 byobtaining a copy of the augmented EHR record for the identified patientfrom the augmented EHR vault 96. An EHR reply 172 is communicated fromthe Aggregator 126 to the Provider 122 identified in the EHR request168. The EHR reply 172 includes a copy of the augmented EHR record forthe identified patient as exists in the augmented EHR vault 96.

Upon receiving the augmented EHR record for the identified patient inthe EHR reply 172, the Provider 122 creates a local record of theaugmented EHR and stores that record in the local memory 134 for thatpatient, if the patient is a new patient. If the patient is an existingpatient, the Provider 122 updates the pre-existing local EHR recordstored in the local memory 134 for that patient with the most currentaugmented EHR record contained in the EHR reply 172.

After updating the local EHR record of the patient with the augmentedEHR record received from the Aggregator 126, and after deliveringHealthcare to the patient, the Provider 122 again updates the local EHRrecord to reflect the Healthcare delivered. That updated EHR record isthen stored in local memory 134. When the

Provider 122 sends a payment request 138 to a Payer 124 to receivecompensation for the Healthcare delivered, the previously describedactions which lead to augmenting the patient's EHR data commence, sothat the updated local EHR record in the local memory 134 is transmittedto the Aggregator 126 as part of a pull reply 156 to the EHR Aggregator126. The most current information from the EHR data received in the pullreply 156 is used by the Aggregator 126 to augment the EHR record of thepatient stored in the augmented EHR vault 96. In this manner, acontemporaneous, comprehensive and augmented EHR record for the patientis established in the augmented EHR vault 96 for each patient and thataugmented EHR record becomes available to use in executing the procedure20 (FIGS. 1A-1D).

The MU-compliant information describing the augmented EHR of the patientis readily available to the Aggregator 126. No initiatives from thepatient or further efforts from the Provider are required to collect andaugment the EHR data of the patient. The payment requests 138 and thepayment request triggers 142 constitute a reliable basis for collecting,aggregating and augmenting EHR data of the patient stored in theaugmented EHR vault 96.

For purposes of clarity of description, each payment request 138, eachpayment request trigger 142, each pull request 152, a each pull reply156, each EHR request 168 and each EHR reply 172 is shown as a separateand direct communication between the entities involved. In actualpractice, these communications are performed over a public communicationnetwork, such as the internet 106 (FIG. 2). Such communications arepossible because of the unique public network addresses of the Providers122, the Payers 124, and the Aggregator 126. These communications,although shown as direct, can occur through intermediate entities suchas clearing houses and health information exchanges.

The Provider status of the Aggregator 126 may be obtained with theconsent of the patient 120 as part of the patient-Provider transaction128, for example. Provider status of the Aggregator under the MUstandards may also be negotiated with governmental regulatory bodies. Tobecome a Provider, the Aggregator must provide Healthcare under the MUstandards, such as, for example, establishing and providing diagnosticand health monitoring services to the patient in his or her home. Thebenefit of having the augmented EHR data available for use by Providersis an incentive for patients to authorize the Aggregator as a Providerin the patient-Provider transaction 128. The Aggregator 126 may alsodirectly obtain authorization as a Provider from the patient. To obtainthe status of a Provider, the Aggregator must obtain the certificationsapplicable to Providers.

In summary, the Basic EHR vault 94 is populated, without patientconsent, by the Aggregator 126 procuring Healthcare information fromPayers. Next, for those patients who have affirmatively agreed to usethe Aggregator 126 as a Provider, the Aggregator 126 procures details ofthe EHR and procedures of the patient from other Providers, using thepayment request as a trigger, and thereby populates the Augmented EHRVault 96 with the procured information. Once the patient engages in thismanner with the Aggregator 126, some of the patients will also provideadditional pathologies or information to populate the genomic vault 98and other vaults 99.

Communication between the Providers 122, the Payers 124 and theAggregator 126 is facilitated by the Health Insurance Portability andAccountability Act of 1996 (HIPAA). HIPPA establishes a standard forElectronic Data Interchange (EDI) between Providers and Payers. The EDIHealthcare Claims Transaction Set (HIPAA Transaction 837) establishes aprevalent and widely utilized template for the components of the paymentrequests 138 from a Provider to a Payer.

The Aggregator 126 can use the ANSI X12N 270/271 Healthcare EligibilityBenefit Inquiry and Response transaction regulations to obtainadditional information about the patient. The Aggregator sends an ANSIX12N 270 request to the Payer with the Payer health identificationnumber (PHIN), patient's name and patient's date of birth. The Payerresponds in a HIPAA 271 communication, which provides the Aggregatorwith the patient's address including city, state and zip code as well asthe patient's gender. The Aggregator may use this enhanced patientidentification information as part of its database to ensure accuratecollection of the EHR data for the patient.

At the present time in United States, there are six Payers who offerHealthcare insurance or Healthcare payment coverage to approximately 170million patients. Those Payers are CMS (Medicare), United Healthcare,Wellpoint, Aetna, Cigna and

Humana. Consequently at the present time, the Aggregator 126 needs onlyto acquire familiarity with a few different formats of payment requests138 to extract information from the payment request triggers 142 whichis beyond the purview of the HIPPA standards.

For pharmacy, dental, medical laboratory and other healthcare entities,there are specific transaction definitions similar to the HIPAA 837. Forexample in a retail pharmacy claim transaction, a National Council forPrescription Drug Programs (NCPDP) telecommunication standard is used asthe basis for EDI payment requests 138 from pharmacy Providers toPayers. The details of these EDI transaction protocols vary but thebasic information communicated is similar, and always includes a patientidentification, a Provider identification, and a basic description ofthe Healthcare delivered.

Aspects of the basic EHR data which the Aggregator may employ in pullrequests, and which are also contained in payment requests 138 andrepeated in payment request triggers 142, include an InternationalClassification of Diseases (ICD) code which indicates the disease orcondition treated by the Provider, a Current Procedural Terminology(CPT) code which describes the medical procedure performed by theProvider on the patient, a National Drug Code (NDC) which describes thedrug prescribed, the dosage of the drug, and the date when theHealthcare was delivered to the patient. The ICD, CPT and NDC codes anddates are a consistent set of definitions utilized by Payers andProviders.

It is advantageous for the historically complete EHR record of thepatient to be available in the augmented EHR vault 96. Augmenting EHRrecord of a patient in response to a payment request ensures that thepatient's EHR record is updated whenever a Provider delivers Healthcareto the patient. There are number of techniques for obtaining historicalEHR data to include in the augmented EHR record.

Payment requests 138 submitted to Payers 124 are typically maintained byPayers for a considerable length of time, for example fourteen years.Consequently, the PHIN for a patient can be used by the Aggregator toaccess the historical basic EHR records of the patient stored by thePayer in connection with previous payment requests. Those historicalrecords can thereafter be used to augment the EHR record, and to sendpull requests 152 to the Providers that delivered the Healthcare.Provided that the historical local EHR records of the Providers areMU-compliant, those records are collected and incorporated in thepatient's augmented EHR record.

Patients can also submit to the Aggregator 126 other records whichcontain information that describes historical Healthcare delivered. TheAggregator 126 will augment the patient's EHR record based on thoserecords. For example, Healthcare delivery information is available froma so-called “super bill” that is generated by a Provider at the time ofdelivering Healthcare. The super bill includes much detail concerningthe Healthcare delivered to the patient, and frequently includes codeswhich are MU-compliant. A Provider may give a copy of the super bill tothe patient, and the patient can then supply the super bill to theAggregator 126. The medical information from the super bill is thenaggregated into the augmented EHR record by the Aggregator.

In those limited circumstances where patients have established andmaintain a personal health record (PHR), the patient may give theAggregator 126 access to the PHR. The medical information contained inthe PHR is then used by the Aggregator to augment the EHR records of thepatient stored in the augmented EHR vault 96.

Only a few laboratory medical service entities and pharmacies cover mostof the laboratory and pharmacy services offered to patients in theUnited States. For laboratory medical services in the United States,Quest Diagnostics and Labcorp presently have the substantial majoritymarket share of non-hospital based laboratory testing. The Aggregator126 can periodically send pull requests 152 to these two companies forlaboratory testing EHR data pertaining to a patient. The informationcontained in any pull reply 156 typically identifies those Providerswhich ordered the medical tests, and the Aggregator can further sendpull requests 152 to those identified Providers. In the case of pharmacyservices, a United States entity known as Surescripts acts as aclearinghouse for electronic prescriptions from a Provider to a retailpharmacy. The significant majority of prescriptions in the United Statesare funneled through Surescripts. The Aggregator can send pull requests152 to Surescripts or to other similar intermediaries by which to obtainaugmented EHR data. This information will again include the identitiesof prescribing Providers to which the Aggregator 126 can send furtherpull requests 152.

Typically and as described above, the Clinical Trial Entity willmaintain its own computer system 91 (FIG. 2) and perform those functionsof designing, enrolling, qualifying and conducting the clinical trial,while the Aggregator will maintain its own computer system 90 (FIG. 2)and perform those functions of aggregating the EHR data of the patients,matching patient etiologies with clinical trial requirements andsoliciting matched patients to participate in the clinical trial, andpossibly assisting the Clinical Trial Entity in enrolling patients inthe clinical trial who respond favorably to solicitations. However, itis also possible that the functions and computer systems of the ClinicalTrial Entity and the Aggregator could be combined and all of thefunctionality described in the present invention performed by a singleentity.

The details of executing the procedure 20, shown in FIGS. 1A-1D, are nowbetter described based on the information explained in connection withFIGS. 2 and 3.

The details of selecting specific clinical trial criteria, shown at 24in FIG. 1A, involve the Administrator and medical experts employed bythe Clinical Trial Entity selecting the specific diseases, humancharacteristics and health and medical conditions which define thepatient for which the new medical therapy is intended to be applied. Apatient with these characteristics and conditions who participates inthe clinical trial will develop the best evidence of efficacy of the newmedical therapy. The clinical trial criteria are selected from among thedescriptions of the characteristics and conditions of patients in themedical records of the patients stored in the vaults 94, 96, 98 and 99.

The Administrator and medical experts employed by the Clinical TrialEntity, initially select the clinical trial criteria at 24. TheAdministrator and medical experts also approve changing the trialcriteria when adjustments of the clinical trial occur at 34, 48, 54, 62,68, 76 and 82. Changing the clinical trial criteria in this mannerfacilitates achieving meaningful outcomes when conducting the clinicaltrial.

The details of comparing patient medical records and the clinical trialcriteria shown at 26, and determining the actual number of suitablepatients with matching criteria shown at 28, involve typicalcomputational activities executed by the Aggregator, such as setoperations (union, intersection and difference) linked by patientidentifications. Many of the procedural stages involved in designing theclinical trial by executing the procedure 20 will be accomplishedwithout specifically identifying the patient. In such cases, for examplewhen procuring patient counts and other associated information, a uniqueanonymized patient identification known only to the Aggregator may serveas the primary key for identifying the patients.

The details involved in extrapolating the actual number of suitablepatients to represent the entire market, shown at 30 (FIG. 1A), isachieved by using statistically representative ratios of the number ofpatients whose medical records are contained in each of the three vaults92, 94 and 96 (FIGS. 2 and 3). An example of developing simplifiedstatistically representative number is explained as follows.

Assume that the specific trial criteria identifies N potentialqualifying patients in the genome vault 96. These N patients directlycorrespond to N patients in the augmented EHR vault 94 and in the basicEHR vault 92, because the more specific medical records of the Npatients in the genome vault would also fall within the less specificinformation contained in the basic EHR vault and in the augmented EHRvault. Specific clinical trial criteria would therefore have astatistically and empirically derived adoption ratio of AR[A] for theaugmented EHR Vault and an adoption ratio of AR[B] for the basic EHRVault. The adoption ratio AR[A] indicates that for these specific Npatients and their profile, there would be AR[A] patients in theaugmented EHR vault for each patient that exists in the genome vault,and there would be AR[B] patients in the basic EHR vault for eachpatient that exists in the augmented EHR vault.

Using these adoption ratios, starting with the N patients in the genomevault that specifically meet the trial criteria, the extrapolated numberof patients (T) for market feasibility would be T={N×AR[A]}×AR[B]. N isthe number of patients in the genomic vault with matching clinical trialcriteria, and N×AR[A] represents the extrapolated number of patients inthe augmented EHR vault with matching clinical trial criteria, and{N×AR[A]}×AR[B] represents the extrapolated number of patients in thebasic EHR vault with matching clinical trial criteria.

N×AR[A] is greater than N because not all patients in the augmented EHRvault have had their genome sequenced and represented in the genomevault. Similarly, the number of patients in the basic EHR vault({N×AR[A]}×AR[B]) is greater than the number of patients in theaugmented EHR vault (N×AR[A]) because not all of the patients in thebasic EHR vault have had their medical records augmented to thespecificity required for inclusion in the augmented EHR vault. The valueT represents the number of individuals within the general populationwhich represent a commercial market for the newly developed therapy.

In this example, the adoption ratios AR[A] and AR[B] vary depending ondisease states, age, gender, geography, income levels, etc. Patternmapping algorithms can cluster variables to predictively refine theadoption ratios. Surveys can also be used to more accurately define theratios.

The details of determining economic feasibility shown at 32 constitutethe starting point to evaluate developing a new medical therapy,particularly a specific medical therapy which branches from a baselinetherapy. The extrapolated number obtained at 30 is compared to thenumber of patients expected to consume the new therapy multiplied by theprofit margin of marketing the new therapy. If profitability isdemonstrated, the feasibility of researching and developing the newtherapy is indicated by an affirmative determination at 32. Thedetermining factor is the number of patients in the general populationwho are potential consumers of the new therapy, as derived at 30.

The determination at 32 involves the extrapolated number obtained at 30and the expected profitability of the new therapy on a per patient basiscompared to the anticipated cost of developing, testing and obtainingmarket approval for the use of the new therapy. If the comparison isinadequate to achieve economic feasibility, as indicated by the no (1)negative determination at 32, a decision is made at 34 to adjust theclinical trial criteria. If after iterations of adjusting the clinicaltrial criteria, economic feasibility is still not achieved, a no (2)negative determination is made at 32. That determination leads to thedecision to wait at 38 and 40, or to terminate the entire procedure 20at 42, as previously described. Of course, if the determination at 32 isaffirmative, indicating favorable economic feasibility, the procedure 20continues.

As a practical matter, once economic feasibility has been determined asindicated by the affirmative determination at 32, the subsequentdeterminations and evaluations within the procedure 20 involve thepracticalities of assuring adequate participation to design, conduct andconclude the clinical trial successfully, while minimizing costs andachieving reliable data by which to evaluate efficacy. Nevertheless, thetest for economic feasibility at 32 repeated in the procedure 20 witheach dynamic adjustment of the clinical trial criteria when designingthe clinical trial. In general, if economic feasibility is notdemonstrated, it is unlikely that the clinical trial will progress tocompletion.

Next in the procedure 20, those suitable patients with matchingcharacteristics and health and medical conditions, i.e. matchingetiologies, that were determined at 26 and 28 are counted at 44 (FIG.1B). The patients counted at 44 are those who are visible within thevaults 94, 96, 98 and 99 (FIG. 2). The patients counted at 44 constitutethe maximum number that can be considered as suitable participants inthe clinical trial under the present set of specific trial criteriaselected at 24.

The number of suitable patients counted at 44 must exceed a minimumthreshold in order to conduct a successful clinical trial, as determinedby the Administrator and medical experts employed by the Clinical TrialEntity. The minimum threshold number of participants necessary toconduct a successful clinical trial is information which theAdministrator and experts employed by the Clinical Trial Entity willdetermine in accordance with previously obtained heuristic experience indesigning clinical trials, or in accordance with normally acceptedstandards for designing and successfully concluding clinical trials. Thesufficiency of the counted number of suitable patients is determined at46, by comparing the counted number of suitable patients at 44 with theminimum number of participants necessary to conduct the clinical trial.The threshold aspects of the determination at 46 center around thepractical aspects of conducting the clinical trial to a successfulcompletion.

If the number of suitable patients counted at 44 does not meet theminimum threshold for a successful clinical trial, as represented by ano (1) negative determination at 46, a decision is made by theAdministrator and experts at 48 to adjust the clinical trial criteriaselected at 24, in order to evaluate whether an adequate number ofsuitable patients exist to conduct a successful clinical trial. Anaffirmative determination at 48 represents the decision to adjust orchange one or more of the specific clinical trial criteria selected at24. The Administrator and experts of the

Clinical Trial Entity must approve the adjustment or change in thespecific clinical trial criteria by selecting new specific clinicaltrial criteria at 24. Of course, no adjustments will be necessary if thenumber of suitable patients initially counted at 44 is adequate, asrepresented by initial affirmative and negative determinations at 46 and48, respectively.

Once the clinical trial criteria has been changed or adjusted, themedical records of the patients are compared to the newly selectedclinical trial criteria by the Aggregator at 26, and the number ofsuitable patients with matching criteria are determined at 28. Economicfeasibility is determined by the Clinical Trial Entity at 30, 32 and 34.The number of suitable patients with etiologies matching the newlyadjusted criteria are counted at 44 and the sufficiency of this numberis again tested at 46 and 48.

Dynamic adjustment of the clinical trial criteria continues in thismanner until the sufficiency threshold at 46 is met, as represented byan affirmative determination at 46. On the other hand, after a number ofiterative attempts at adjusting the clinical trial criteria to achievean adequate number of suitable patients proves impossible to accomplish,a no (2) negative determination at 46 leads to a choice by the ClinicalTrial Entity of whether to wait at 38 for a predetermined amount of timeto expire as determined at 40, or to end the procedure 20 at 42. Thebenefit of waiting is that new patients with medical records matchingthe adjusted clinical trial criteria might become available in thedatabase, either because of the addition of new patients in the vaults94, 96, 98 and 99 (FIG. 2), or because the characteristics and healthconditions of enough existing patients in the vaults 94, 96, 98 and 99(FIG. 2) has changed.

Although the dynamic adjustment at 46 and 48 described above is in termsof increasing the number of suitable patients, the same type of dynamicadjustment may be employed to reduce the number of suitable patients, ifan excessive number of such patients are counted.

Upon meeting the threshold at 46 of attaining an appropriate number ofsuitable patients with matching etiologies, the procedure 20 moves to 50and 52, where the number of suitable patients identified at 44 isevaluated by the Administrator and experts employed by the ClinicalTrial Entity as constituting an adequate pool of potential participantsto qualify for and successfully complete the clinical trial. Theevaluation at 50 and the determination at 52 involve applying areduction factor to the number of suitable patients counted at 44. Thereduction factor takes into account that less than all of the suitablepatients counted at 44 will qualify for and complete the clinical trial.For example, not all of the suitable patients will respond to asolicitation to participate, and of those who do respond favorably, notall will enroll as participants. Not all of those suitable patients whoenroll as participants will qualify as participants under the verystrict qualification laws and regulations applicable to clinical trials.Of those qualified and enrolled patients, a certain number will drop outof the clinical trial before it is completed. All of these reductionsare taken into account in the reduction factor applied at 50. Thereduction factor is an estimate, and is typically based on the empiricalexperience gained by the Clinical Trial Entity in designing andconducting clinical trials.

The purpose of the evaluation at 50 and the determination at 52 is tomake a practical prediction of the participation, before any suitablepatients are solicited for participation. By making the evaluation at 50and the determination at 52, before soliciting the suitable patients,inefficiencies, delays and failures are avoided when designing the laterstages of the clinical trial and conducting the clinical trial. Theevaluation at 50 and the determination at 52 are primarily matters ofpractical efficiency in designing and conducting the clinical trial.

The determination at 52 is whether the number of qualified patientsidentified at 44 meets a threshold after the reduction factor has beenapplied. If the number is inadequate to achieve an adequately sized poolof qualified patients, or if the pool of qualified patients isexcessive, as determined by a no (1) negative determination at 52, anaffirmative decision at 54 results in adjusting the clinical trialcriteria with the expectation of increasing or decreasing the pool ofsuitable patients, as the case may be. Increasing the pool of suitablepatients facilitates successfully completing the clinical trial, whiledecreasing the pool of suitable patients reduces the cost of theclinical trial.

If after iterations of adjusting the clinical trial criteria in themanner described does not achieve an adequate pool of suitable patients,a no (2) negative determination at 32 will be made. That determinationat 32 leads to the decision to wait at 38 and 40, or to end theprocedure 20 at 42. Of course, if the dynamic adjustment of the clinicaltrial criteria results in an adequate pool of suitable patients, anaffirmative determination at 52 results in a determination at 54.Thereafter the suitable patients are identified at 55, and theidentified patients are solicited by the Liaison of the Aggregator toparticipate in the clinical trial at 56. The Liaison solicits theidentified patients to protect patient privacy. If the solicited patientagrees to participate in the clinical trial and also agrees to thedisclosure of his or her confidential and protected medical informationto the Clinical Trial Entity, communications with each consentingsolicited patient may be assumed by the Administrator of the ClinicalTrial Entity. This solicitation of the patient by the Liaison 102 ispreferably fully automated. A favorable response from the patient nexttriggers an automated process that links the patient with the ClinicalTrial Entity.

Directly soliciting the identified patients at 56 is the first instancein the procedure 20 where patients have any notice or informationconcerning the possibility of their participation in a clinical trial.Designing the previous stages of the clinical trial in the mannerdescribed permits the Clinical Trial Entity to reform the clinical trialcriteria without involving patients and without disclosure of theclinical trial. Dynamically adjusting the scope of the clinical trial toachieve the best efficiency without compromising the end results, anddoing so while maintaining secrecy, are commercial benefits which theClinical Trial Entity typically wishes to preserve.

As part of the patient's relationship with the Aggregator (126, FIG. 3),the patient provides an internet address or a physical address that isused by the Liaison of the Aggregator to communicate with the patient.This address is subsequently used at 56 to inform a patient of theapplicability of a clinical trial and solicit his or her agreement toparticipate in the trial. The Clinical Trial Entity is not involved inthis solicitation. The Aggregator, acting as a Provider to the patient,makes this solicitation. In this regard the solicitation complies withpatient privacy laws and regulations. As an important consequence, thisdirect, non-intermediated, and typically automated solicitation occurswithout compromising the identity or protected health information of thepatient.

Directly soliciting the identified patients at 56 involves the Liaisonof the Aggregator sending each identified patient an invitation toparticipate in the clinical trial. The solicitation is algorithmicallygenerated and preferably sent electronically directly to the patientover the internet 106 (FIG. 2). The Liaison will issue solicitations tothose identified patients who do not communicate over the internet usingother forms of communication, such as regular mail. The efficiency ofdesigning the clinical trial is greatly facilitated if the identifiedpatients have the capability of communicating over the internet.

Directly soliciting participation of the patients at 56 is possiblebecause the Aggregator is a Provider, and Providers may communicatedirectly with patients without intermediation. Eliminatingintermediation by use of direct communication, while preserving patientprivacy, increases the efficiency of designing the clinical trial.

Favorable responses to the solicitations issued at 56 are accumulatedand counted at 58. If a solicited patient elects not to participate,that patient is not further solicited. If any solicited patient does notrespond within a predetermined time interval, that patient is againsolicited. After the expiration of another time interval that wouldindicate that the solicited patient is not interested in participating,no further attempt is made to solicit that patient.

Periodically the counted number of favorable responses at 58 is testedagainst a threshold number at 60 (FIG. 1C). The threshold number used at60 will be established by the Administrator and experts of the ClinicalTrial Entity, taking into account empirical experience, heuristicsand/or normally accepted standards concerning the extent ofparticipation required in successful clinical trials, at this stage ofdesigning the clinical trial. If the number of favorably respondingpatients is inadequate to conduct the clinical trial, or if there are anexcessive number of patients responding favorably to the solicitation,as determined by a no (1) negative determination at 60, an affirmativedecision is made at 62 to adjust the clinical trial criteria. Adjustingthe clinical trial criteria will result in identifying a differentnumber of qualified patients at 44, followed by evaluating at 30 and 32and 50 and 52 whether the number of newly identified patients issufficient to constitute an adequate pool of potential participants.

Additional suitable patients identified from the dynamic adjustment ofthe clinical trial criteria are then sent invitations to participate at56 by the Liaison. Those additional patients who respond favorably arecounted at 58. The determination is thereafter made at 60 as to whether,with inclusion of the additional favorably responding patients, anadequate pool of favorably responding patients exists at this stage ofthe procedure 20 to conduct a clinical trial. If not, the dynamicadjustment continues with an affirmative determination at 62.

On the other hand, if it is desired to reduce the number of favorablyresponding patients, an affirmative determination at 62 results inadjusting the clinical trial criteria by increasing the specificity ofthose criteria. The adjustment will eliminate those ones of thepreviously favorably responding patients who do not meet the changedcriteria of the increased specificity. Those who do not meet theincreased specificity of the clinical trial criteria are counted at 58.After an affirmative determination at 60, notices are then sent to thosefavorably responding patients who do not meet the adjusted clinicaltrial criteria, informing them that their participation in the clinicaltrial will not be required. Notifying patients that their participationwill no longer be required is subsumed within the solicitation at 56.

If after iterations of adjusting the clinical trial criteria in thismanner, adequate enrollment still has not been achieved, a no (2)negative determination at 60 leads to the decision by the Administratorand experts to wait at 38 and 40, or to terminate the procedure 20 at42. Of course, if the determinations at 60 and 62 are affirmative andnegative, respectively, indicating that adequate enrollment has beenachieved, the procedure 20 continues to 64.

At 64 and 66, an evaluation is made by the Clinical Trial Entity as towhether the number of favorably responding patients counted at 58constitutes an adequate pool of potential participants in the clinicaltrial to result in the successful enrollment, qualification andcompletion of the clinical trial. The evaluation at 64 and thedetermination at 66 involves applying a reduction factor to the numberof favorably responding patients counted at 58. The reduction factor isan estimate which takes into account that less than all of the favorablyresponding patients counted at 58 will actually enroll as participants,will qualify as participants under the very strict qualification lawsand regulations applicable to clinical trials, and will complete theclinical trial. All of these reductions are taken into account in thereduction factor applied at 64 by the Clinical Trial Entity. Thereduction factor is an estimate, and is typically based on the empiricalexperience gained from designing and conducting clinical trials.

The reduction factor applied at 64 may differ from the reduction factorapplied at 50, even though both reduction factors involve similarconsiderations. The reduction factor applied at 64 may be refined basedon the degree of response to the solicitations represented by theresponses counted at 58. This information was not available at the timethat the reduction factor was applied at 50. Also, experience indesigning clinical trials may demonstrate that adjustments to thereduction factors are appropriate at different stages of designing theclinical trial, based on different degrees of seriousness or imminency,or other factors that come into play and achieve significance as theclinical trial design nears completion.

The purpose of the evaluation at 64 and the determination at 66 is toenable the Clinical Trial Entity to make a practical prediction of thenumber of favorably responding patients who will actually enroll asparticipants in the clinical trial, before any of the favorablyresponding patients are solicited to enroll as participants. By makingthe evaluation at 64 and the determination at 66 before attempting toenroll the favorably responding patients, delays and inefficiencies areavoided. Some of the favorably responding patients will have changedtheir mind about participation in the clinical trial between the timewhen they favorably responded to a solicitation to participate and whenthey are solicited to enroll. The pool of favorably responding patientsshould be of adequate size to allow some of the favorably respondingpatients to withdraw from participation. The evaluation at 64 and thedetermination at 66 are primarily matters of practical efficiency indesigning the clinical trial at this stage of the procedure 20, andensure that the subsequent design activities are efficiently conductedwithout delaying or compromising the clinical trial.

The determination at 66 is whether the number of favorably respondingpatients counted at 58 meets a threshold after the reduction factor hasbeen applied by the Clinical Trial Entity at this stage of designing theclinical trial. If the number is inadequate to achieve an adequatelysized pool of patients who are likely to enroll and qualify for theclinical trial, or if the pool of patients is excessive, as determinedby a no (1) negative determination at 66, an affirmative decision at 68results in dynamically adjusting the clinical trial criteria with theexpectation of increasing or decreasing (as the case may be) the pool offavorably responding patients who are likely to enroll. Increasing ordecreasing the pool of favorably responding patients who are likely toenroll is desirable at this stage of the procedure 20 to reduce the costof the clinical trial while still obtaining reliable results.

If after iterations of adjusting the clinical trial criteria in thismanner and an adequate pool of identified and qualified patients who arelikely to enroll has still not been achieved, a no (2) negativedetermination at 66 leads to the decision to wait at 38 and 40 or to endthe procedure 20 at 42. Of course, respectively affirmative and negativedeterminations at 66 and 68 indicate that the pool of favorablyresponding patients who are likely to enroll is predicted as adequate toqualify and complete the clinical trial successfully.

The adjustment achieved as a result of the actions 64, 66 and 68 reducesthe cost of the clinical trial. There is administrative cost involved inattempting to enroll and qualify patients as participants. Enrolling andqualifying patients generally requires human if not face-to-faceinteraction to arrange for and agree on appropriate terms forcompensation. Paperwork, including informational forms and consents, aretypically required and must be obtained. Enrolling and qualifying nomore patients than is necessary to achieve meaningful results from theclinical trial facilitates the efficiency and reduces the cost ofconducting the clinical trial.

Enrolling patients as participants in the clinical trial at 70 involvessending an invitation to enroll to each favorably responding andqualified patient in the pool previously established at 58, 60, 62, 64,66 and 68. The enrollment invitation is preferably sent electronicallyto those patients communicating over the internet 106 (FIG. 2). However,in those cases where some of the patients do not communicate over theinternet, the invitations may be issued using other forms ofcommunication, such as regular mail.

A very important part of enrollment involves detailed contact tocomplete the terms of the enrollment. In addition to reaching anagreement with the patient to participate in the clinical trial,enrollment involves managing and completing certain qualificationrequirements as shown at 71. The qualification requirements arespecified by law and regulation. These qualification requirements gowell beyond the etiological conditions of the patients described in thedatabase at 22. Qualification requirements involve such things as familysupport for the participant, adequate transportation for the patient toand from examinations and appointments, access to doctors andpharmacies, conflicts of interest and many other factors. To assure thata patient attempting to enroll meets these qualification requirements,human contact actions are required by the Clinical Trial Entity. Usuallythese human interactions are performed by the Administrator. Only thosepatients who successfully qualify are actually enrolled at 70. TheAggregator can also automatically screen and enroll patients for theClinical Trial Entity and thereby reduce the manual interactions at thisstage of the enrollment process.

Enrolling patients at 70 may be the first instance where the identity ofthe Clinical Trial Entity is disclosed. Control over the disclosure ofclinical trials has commercial value, and minimizing the number ofpatients involved by use of the dynamic adjustment aspect of theprocedure 20 helps protect that control and commercial value.

The number of enrolled participants is accumulated and counted at 72.The number of enrolled participants counted at 72 is evaluated at 74against a threshold number (FIG. 1D). The threshold number used at 74will be established by the

Administrator and experts employed by the Clinical Trial Entity. If thenumber of enrolled patients counted at 72 is inadequate to complete theclinical trial, or if there are an excessive number of patientsenrolled, as determined by a no (1) negative determination at 74, anaffirmative decision at 76 adjusts the clinical trial criteria toachieve the desired level of enrollment. Under this circumstance,adjusting the clinical trial criteria will result in progressing throughthe procedure 20, in the manner previously described.

The additional patients identified for enrollment as a result of thedynamic adjustment are then sent invitations to enroll at 70. Thosefavorably responding patients are counted at 72. The determination isthereafter made at 74 by the Clinical

Trial Entity whether adequate participants have enrolled to conduct theclinical trial. If it is desired to reduce the number of enrolledpatients, after adjusting the clinical trial criteria, notices are sentto any previous enrolled patients who have been eliminated as a resultof the dynamic adjustment, informing them that their participation inthe clinical trial is not be required. Notifying the previous enrolledpatients that their participation will no longer be required is subsumedwithin the enrollment activity at 70. Of course, those previous enrolledpatients whose participation is no longer required are subtracted fromthe count at 72.

If after iterations of adjusting the clinical trial criteria in thismanner, and adequate enrollment still has not been achieved, a no (2)negative determination at 74 by the Clinical Trial Entity leads to thedecision to wait at 38 and 40 or to the end procedure 20 at 42, aspreviously described. Of course, if the determination at 74 isaffirmative, indicating that the adequate enrollment has been achieved,the procedure 20 moves to 78 and 80.

At 78 and 80, an evaluation is made by the Clinical Trial Entity ofwhether the number of enrolled participants counted at 72 constitutes anadequate pool of participants to successfully complete the clinicaltrial. Not all of the enrolled participants in the clinical trial willcomplete the clinical trial, due to such things as death, sickness,health condition changes, geographical movement, and lack of interest.The evaluation at 78 involves applying a reduction factor to the numberof enrolled participants counted at 72. The reduction factor is anestimate, and is typically based on empirical experience in observingthe number of enrolled and qualified participants who typically completea clinical trial.

The determination at 80 is whether the number of participants enrolledcounted at 72, as reduced by the reduction factor set by the ClinicalTrial Entity, meets a sufficient threshold. If the number is inadequateto achieve an adequately sized pool of enrolled and qualifiedparticipants, or if the pool of enrolled and qualified participants isexcessive, a no (1) negative determination at 80 results in anaffirmative decision at 82 to adjust the clinical trial criteria withthe expectation of increasing or decreasing the pool of enrolled andqualified participants. Decreasing the pool of enrolled participants isdesirable to reduce the cost of the clinical trial under circumstanceswhere efficacy can still be reliably determined. Increasing the pool ofenrolled participants is desirable to assure that the clinical trial canbe successfully completed.

The purpose of the evaluation at 78 and the determination at 80 is toenable the Clinical Trial Entity make a practical prediction of thenumber of qualified participants to complete the clinical trial, beforethe clinical trial is commenced at 84. By making the determinations at78 and 80, before starting the clinical trial, delays in completing theclinical trial or a premature termination of the clinical trial isavoided because enough enrolled and qualified participants exist toovercome the various factors which may prevent some of the participantsfrom completing the clinical trial.

If after iterations of adjusting the clinical trial criteria in thismanner and an adequate pool of enrolled and qualified participants hasstill not been achieved, a no (2) negative determination at 66 leads toa decision by the Clinical Trial Entity to wait at 38 and 40, or to endthe procedure 20 at 42. Of course, if the determinations at 80 and 82are affirmative and negative, respectively, indicating that the pool ofenrolled and qualified participants is adequate to successfully completethe clinical trial, the design stages of the clinical trial procedure 20have been completed. The clinical trial is thereafter conducted at 84 bythe entity which actually conducts the clinical trial. The entityconducting the clinical trial may or may not be the Clinical TrialEntity, since in some cases the Clinical Trial Entity sets up the rightpatients to commence the trial and then hands over the remainder of theclinical trial to be conducted by another entity.

The previous description of the procedure 20 include instances at 46,50, 52, 60, 74, and 80 which involve determining and evaluating whethera number of patients is acceptable at each of the different stages forsoliciting participation, enrolling participants and completing theclinical trial. The determinations at 46, 60 and 74 are made by theClinical Trial Entity and involve a comparison of actual counted numbersrelative to threshold numbers. The evaluations at 50, 64 and 78 involvepredictions based on counted numbers, again made by the Clinical TrialEntity. Instead of separate determinations and evaluations, the actionsat 46, 50 and 52, and at 60, 64 and 66, and at 74, 78 and 80, could eachbe combined into a single determination which both counts and evaluatesor predicts the outcome, before making a dynamic adjustment of theclinical trial criteria.

Executing the complete procedure 20 results in designing a clinicaltrial under circumstances which achieve economic feasibility, efficiencyand cost reduction. Economic feasibility accurately predicts whether thecost and expense of researching and developing a new medical therapy isjustified. The efficiency and cost reduction arise from the ability todynamically adjust the clinical trial criteria and thereby change thenumber of participants to an optimal number of not substantially moreand not substantially less than the number of participants required toefficiently complete a clinical trial which demonstrates efficacy.Dynamic adjustment also reduces the cost of the clinical trial, andenhances or ensures the probability of completing a clinical trial whichyields results that allow the efficacy of a newly developed medicaltherapy to be effectively and efficiently evaluated. This level ofnon-intermediated identification, solicitation and enrollment, whichcomplies with patient privacy and confidentiality laws and regulations,is believed to have been previously unavailable to clinical trialentities.

In addition to dynamic adjustment, the invention permits directlypushing clinical trial information and solicitations to qualifiedpatients in a specifically targeted manner while maintaining the privacyand confidentiality of the patient. A targeted push of this nature is asignificant improvement when compared with current techniques of pullingin patients based on a broad notice of a trial and the expectation thatpatients will find their way to the clinical trial on their owninitiative or through an intermediated solicitation by a Provider. Thecombined status of the Aggregator, both as an Aggregator of fulletiologies of many millions of patients, for example, and as a Providerof Healthcare to the same number of patients, allows the Aggregator toaccess the etiology Vaults for matches and then, in a dis-intermediatedmanner, solicit matched and qualified patients for enrollment. Thecombined Aggregator/Provider status permits these actions, with accessto full etiologies of patients, while maintaining patient privacy andcompliance with requirements as required by law.

These benefits are particularly important when a baseline therapy isextended or altered to treat patients with more specific etiologicalcharacteristics. In such circumstances, the clinical trial must beconducted using very specific clinical trial criteria to address deeplevels of specificity of etiologies. Market feasibility is moreuncertain under these circumstances, and suitable participants for theclinical trial are considerably reduced in number and much moredifficult to identify and recruit. Iteratively adjusting differentlevels of specificity in terms of market feasibility, ready electronicaccessibility and rapid enrollment facilitates developing genomicallyspecific therapies. The procedure 20 facilitates overcoming thesepractical hurdles at all the stages involved in designing the clinicaltrial, with efficiency not previously available in other techniques fordesigning clinical trials. This efficiency allows for the current annualnumber of fifty thousand clinical trials involving about ten millionparticipants to scale up to millions of annual clinical trials engaginghundreds of millions of participants. This scale will be necessary asbaseline and other therapies are customized to treat more specificetiological and genomic variations.

Another benefit of the procedure 20 is that it is also scalable in termsof the size of the clinical trial conducted. Clinical trials with largenumber of participants are processed as straightforwardly with theprocedure 20 as smaller clinical trials with fewer participants, all ofwhich is facilitated by the automated processing and communicationcapabilities of the procedure 20.

The benefits and improvements of the present invention createsignificant improvements in clinical trial design, resulting in partfrom the ability to aggregate and utilize the medical records of amassive number of patients on a continuous and timely updated basis.This ability is made possible as a result of recognizing that themedical records can be aggregated by an entity which achieves the statusof a Provider and which updates those medical records in response topayment requests sent by Providers to Payers, in compliance with patientprivacy and confidentiality laws and regulations, as discussed in moredetail in U.S. patent application Ser. No. 13/839,539. Many otherbenefits and improvements will be apparent upon gaining a fullappreciation of the present invention.

The detail of the above description constitutes a description of apreferred example of implementing the invention. The detail of thepreceding description is not intended to limit the scope of theinvention except to the extent explicitly incorporated in the followingclaims. The scope of the invention is defined by the following claims.

The invention claimed is:
 1. A method of designing a clinical trial,comprising: aggregating patient medical records of multiple patients ina database, the medical record of each patient in the database includinginformation describing characteristics and health conditions of eachpatient; establishing the characteristics and health conditions in thedatabase for a first group of patients by collecting basic EHR data ofeach patient from a Payer who previously compensated a Provider fordelivering Healthcare to each patient in the first group; establishingthe characteristics and health conditions in the database for a secondgroup of patients by collecting EHR data from a Provider for eachinstance of the Provider delivering Healthcare to the patient inresponse to the Provider submitting a payment request to a Payer, andaggregating the collected EHR data for each patient of the second groupwith any basic EHR data for each patient of the second group to createaugmented EHR data for each patient in the second group, the patients inthe second group having a relatively higher degree of specificity ofcharacteristics and health conditions than the patients in the firstgroup; selecting clinical trial criteria for participants in theclinical trial from among the characteristics and health conditions ofpatients in the first and second groups; accessing the database toidentify suitable patients as participants in the clinical trial whohave characteristics and health conditions which match the selectedclinical trial criteria; and designing the clinical trial by referenceto the identified qualified patients.
 2. A method as defined in claim 1,further comprising: selecting the clinical trial criteria to include atleast one characteristic and health condition specific to patients inthe second group; determining the relative number of patients in each ofthe first and second groups; identifying suitable patients from thesecond group as participants in the clinical trial who havecharacteristics and health conditions which match the clinical trialcriteria; and determining feasibility for marketing a newly developedtherapy to be tested by a clinical trial of identified patients obtainedfrom the second group, by multiplying the number of identified patientsin the second group by a ratio of the number of patients in the firstgroup relative to the number of patients in the second group.
 3. Amethod as defined in claim 1, further comprising: establishing thecharacteristics and health conditions in the database for a third groupof patients by including genomic information for each patient of thethird group with the augmented EHR data for each patient of the secondgroup, the patients in the third group having a higher degree ofspecificity of characteristics and health conditions than the patientsin the second group.
 4. A method as defined in claim 3, furthercomprising: selecting the clinical trial criteria to include at leastone characteristic and health condition specific to patients in thethird group; determining the relative number of patients in each of thefirst, second and third groups; identifying suitable patients from thethird group as participants in the clinical trial who havecharacteristics and health conditions which match the clinical trialcriteria; and determining feasibility for marketing a newly developedtherapy to be tested by a clinical trial of identified patients obtainedfrom the second group, by multiplying the number of identified patientsin the third group by a ratio of the number of patients in the secondgroup relative to the number of patients in the third group andthereafter multiplying that result by a ratio of the number of patientsin the first group relative to the number of patients in the secondgroup.
 5. A method as defined in claim 1, further comprising:identifying suitable first patients in the database who havecharacteristics and health conditions which match the selected clinicaltrial criteria; determining that the number of identified suitable firstpatients is inadequate to continue designing the clinical trial;changing at least one of the characteristics or health conditions of theclinical trial criteria to create reformed clinical trial criteria;identifying suitable second patients from the database who havecharacteristics and health conditions which match the reformed clinicaltrial criteria, the second patients differing in number from the firstpatients; and designing the clinical trial by reference to the secondpatients.
 6. A method as defined in claim 5, further comprising:applying the aforesaid actions in at least one of a first stage ofdesigning the clinical trial which includes soliciting suitable patientsto participate in the clinical trial, and in a second stage of designingthe clinical trial which includes enrolling favorably respondingsolicited patients as participants in the clinical trial, and in a thirdstage of designing the clinical trial which includes evaluating whetheradequate enrolled patients will complete the clinical trial.
 7. A methodas defined in claim 5, further comprising: applying the aforesaidactions in each of a first stage of designing the clinical trial whichincludes soliciting suitable patients to participate in the clinicaltrial, and in a second stage of designing the clinical trial whichincludes enrolling favorably responding solicited patients asparticipants in the clinical trial, and in a third stage of designingthe clinical trial which includes evaluating whether adequate enrolledpatients will complete the clinical trial.
 8. A method as defined inclaim 5, further comprising: determining that the number of identifiedpatients is inadequate to continue designing the clinical trial in atleast one of a first stage of designing the clinical trial whichincludes soliciting suitable patients to participate in the clinicaltrial, and in a second stage of designing the clinical trial whichincludes enrolling favorably responding solicited patients asparticipants in the clinical trial, and in a third stage of designingthe clinical trial which includes evaluating whether adequate enrolledpatients will complete the clinical trial; continuously updating thepatient medical records in the database; waiting for the patient medicalrecords to update after determining that the number of patients isinadequate; identifying patients from the database who havecharacteristics and health conditions which match the clinical trialcriteria after the patient records have updated; and designing theclinical trial by reference to the patients identified after the patientrecords have updated.
 9. A method as defined in claim 1, furthercomprising: identifying suitable first patients in the database who havecharacteristics and health conditions which match the selected clinicaltrial criteria; determining that the number of identified suitable firstpatients is inadequate to continue designing the clinical trial;changing at least one of the characteristics or health conditions of theclinical trial criteria to create first reformed clinical trialcriteria; identifying suitable second patients from the database whohave characteristics and health conditions which match the firstreformed clinical trial criteria, the second patients differing innumber from the first patients; determining that the number ofidentified suitable second patients is inadequate to continue designingthe clinical trial; again changing at least one of the characteristicsor health conditions of the clinical trial criteria to create secondreformed clinical trial criteria; identifying suitable third patientsfrom the database who have characteristics and health conditions whichmatch the second reformed clinical trial criteria, the third patientsdiffering in number from the first patients and the second patients; anddesigning the clinical trial by reference to the third patients.
 10. Amethod as defined in claim 9, further comprising: applying the aforesaidactions in at least one of a first stage of designing the clinical trialwhich includes soliciting suitable patients to participate in theclinical trial, and in a second stage of designing the clinical trialwhich includes enrolling favorably responding solicited patients asparticipants in the clinical trial, and in a third stage of designingthe clinical trial which includes evaluating whether adequate enrolledpatients will complete the clinical trial.
 11. A method as defined inclaim 9, further comprising: applying the aforesaid actions in each of afirst stage of designing the clinical trial which includes solicitingsuitable patients to participate in the clinical trial, and in a secondstage of designing the clinical trial which includes enrolling favorablyresponding solicited patients as participants in the clinical trial, andin a third stage of designing the clinical trial which includesevaluating whether adequate enrolled patients will complete the clinicaltrial.
 12. A method as defined in claim 9, further comprising:determining that the number of identified patients is inadequate tocontinue designing the clinical trial in at least one of a first stageof designing the clinical trial which includes soliciting suitablepatients to participate in the clinical trial, and in a second stage ofdesigning the clinical trial which includes enrolling favorablyresponding solicited patients as participants in the clinical trial, andin a third stage of designing the clinical trial which includesevaluating whether adequate enrolled patients will complete the clinicaltrial; continuously updating the patient medical records in thedatabase; waiting for the patient medical records to update afterdetermining that the number of patients is inadequate; identifyingpatients from the database who have characteristics and healthconditions which match the clinical trial criteria after the patientrecords have updated; and designing the clinical trial by reference tothe patients identified after the patient records have updated.
 13. Amethod as defined in claim 1, further comprising: identifying suitablefirst patients in the database who have characteristics and healthconditions which match the selected clinical trial criteria; determiningthat the number of identified suitable first patients is inadequate tocontinue designing the clinical trial; continuously updating the patientmedical records in the database; waiting for the patient medical recordsto update after determining that the number of first patients isinadequate; identifying suitable second patients from the database whohave characteristics and health conditions which match the clinicaltrial criteria after the patient records have updated; and designing theclinical trial by reference to the suitable second patients identifiedafter the patient records have updated.
 14. A method as defined in claim13, further comprising: applying the aforesaid actions in at least oneof a first stage of designing the clinical trial which includessoliciting suitable patients to participate in the clinical trial, andin a second stage of designing the clinical trial which includesenrolling favorably responding solicited patients as participants in theclinical trial, and in a third stage of designing the clinical trialwhich includes evaluating whether adequate enrolled patients willcomplete the clinical trial.
 15. A method as defined in claim 13,further comprising: applying the aforesaid actions in each of a firststage of designing the clinical trial which includes soliciting suitablepatients to participate in the clinical trial, and in a second stage ofdesigning the clinical trial which includes enrolling favorablyresponding solicited patients as participants in the clinical trial, andin a third stage of designing the clinical trial which includesevaluating whether adequate enrolled patients will complete the clinicaltrial.
 16. A method as defined in claim 13, further comprising:identifying suitable first patients in the database who havecharacteristics and health conditions which match the selected clinicaltrial criteria; determining that the number of identified suitable firstpatients is inadequate to continue designing the clinical trial;changing at least one of the characteristics or health conditions of theclinical trial criteria to create reformed clinical trial criteria;identifying suitable second patients from the database who havecharacteristics and health conditions which match the reformed clinicaltrial criteria after the patient medical records have updated, thesecond patients differing in number from the first patients; anddesigning the clinical trial by reference to the second patients.